andreasjansson
/
plasma
Generate plasma shader equations
Prediction
andreasjansson/plasma:e636a18b4eb62730cf7a9706b65a5650b1917a15a0ee80499b45f27a673ad633ID575sdydbicj4wf5qynb3sui5z4StatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
{}Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "andreasjansson/plasma:e636a18b4eb62730cf7a9706b65a5650b1917a15a0ee80499b45f27a673ad633", { input: {} } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run("andreasjansson/plasma:e636a18b4eb62730cf7a9706b65a5650b1917a15a0ee80499b45f27a673ad633") # The andreasjansson/plasma model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/andreasjansson/plasma/api#output-schema print(item, end="")To learn more, take a look at the guide on getting started with Python.
Run andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "e636a18b4eb62730cf7a9706b65a5650b1917a15a0ee80499b45f27a673ad633", "input": {} }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
vec2 effect(vec2 p, float i, float time) { return vec2(cos(i * length(p.x + p.y) + sin(time)), sin(i * length(p.x - p.y) + cos(time))); }{ "completed_at": "2023-12-05T15:00:51.280026Z", "created_at": "2023-12-05T15:00:49.202774Z", "data_removed": false, "error": null, "id": "575sdydbicj4wf5qynb3sui5z4", "input": {}, "logs": "from_string grammar:\nroot ::= [v] [e] [c] [2] [ ] [e] [f] [f] [e] [c] [t] [(] [v] [e] [c] [2] [ ] [p] [,] [ ] [f] [l] [o] [a] [t] [ ] [i] [,] [ ] [f] [l] [o] [a] [t] [ ] [t] [i] [m] [e] [)] [ ] [{] [<U+000A>] [ ] [ ] return-statement [<U+000A>] [}]\nreturn-statement ::= [r] [e] [t] [u] [r] [n] [ ] vec2-expression [;]\nvec2-expression ::= single-vec2-expression | single-vec2-expression operation vec2-expression\nsingle-vec2-expression ::= [v] [e] [c] [2] [(] scalar-expression [,] [ ] scalar-expression [)]\noperation ::= [ ] [+] [ ] | [ ] [-] [ ] | [ ] [*] [ ] | [ ] [/] [ ] \nscalar-expression ::= single-scalar-expression | single-scalar-expression operation scalar-expression\nsingle-scalar-expression ::= float-literal | variable | math-func [(] math-arg [)]\nfloat-literal ::= float-literal_11 [.] float-literal_12\nvariable ::= [p] [.] [x] | [p] [.] [y] | [i] | [t] [i] [m] [e] \nmath-func ::= [s] [i] [n] | [c] [o] [s] | [t] [a] [n] | [l] [e] [n] [g] [t] [h] | [s] [q] [r] [t] | [e] [x] [p]\nmath-arg ::= [p] [.] [x] | [p] [.] [y] | scalar-expression\nfloat-literal_11 ::= [0-9] float-literal_11 | [0-9] \nfloat-literal_12 ::= [0-9] float-literal_12 | [0-9] \nLlama.generate: prefix-match hit\nllama_print_timings: load time = 289.48 ms\nllama_print_timings: sample time = 1005.82 ms / 63 runs ( 15.97 ms per token, 62.64 tokens per second)\nllama_print_timings: prompt eval time = 0.00 ms / 1 tokens ( 0.00 ms per token, inf tokens per second)\nllama_print_timings: eval time = 872.28 ms / 63 runs ( 13.85 ms per token, 72.22 tokens per second)\nllama_print_timings: total time = 2021.73 ms", "metrics": { "predict_time": 2.046198, "total_time": 2.077252 }, "output": [ "v", "ec", "2", " effect", "(", "vec", "2", " p", ",", " float", " i", ",", " float", " time", ")", " {", "\n", " ", " return", " vec", "2", "(", "cos", "(", "i", " *", " length", "(", "p", ".", "x", " +", " p", ".", "y", ")", " +", " sin", "(", "time", ")),", " sin", "(", "i", " *", " length", "(", "p", ".", "x", " -", " p", ".", "y", ")", " +", " cos", "(", "time", ")));", "\n", "}" ], "started_at": "2023-12-05T15:00:49.233828Z", "status": "succeeded", "urls": { "stream": "https://streaming-api.svc.us.c.replicate.net/v1/predictions/575sdydbicj4wf5qynb3sui5z4", "get": "https://api.replicate.com/v1/predictions/575sdydbicj4wf5qynb3sui5z4", "cancel": "https://api.replicate.com/v1/predictions/575sdydbicj4wf5qynb3sui5z4/cancel" }, "version": "e636a18b4eb62730cf7a9706b65a5650b1917a15a0ee80499b45f27a673ad633" }Generated infrom_string grammar: root ::= [v] [e] [c] [2] [ ] [e] [f] [f] [e] [c] [t] [(] [v] [e] [c] [2] [ ] [p] [,] [ ] [f] [l] [o] [a] [t] [ ] [i] [,] [ ] [f] [l] [o] [a] [t] [ ] [t] [i] [m] [e] [)] [ ] [{] [<U+000A>] [ ] [ ] return-statement [<U+000A>] [}] return-statement ::= [r] [e] [t] [u] [r] [n] [ ] vec2-expression [;] vec2-expression ::= single-vec2-expression | single-vec2-expression operation vec2-expression single-vec2-expression ::= [v] [e] [c] [2] [(] scalar-expression [,] [ ] scalar-expression [)] operation ::= [ ] [+] [ ] | [ ] [-] [ ] | [ ] [*] [ ] | [ ] [/] [ ] scalar-expression ::= single-scalar-expression | single-scalar-expression operation scalar-expression single-scalar-expression ::= float-literal | variable | math-func [(] math-arg [)] float-literal ::= float-literal_11 [.] float-literal_12 variable ::= [p] [.] [x] | [p] [.] [y] | [i] | [t] [i] [m] [e] math-func ::= [s] [i] [n] | [c] [o] [s] | [t] [a] [n] | [l] [e] [n] [g] [t] [h] | [s] [q] [r] [t] | [e] [x] [p] math-arg ::= [p] [.] [x] | [p] [.] [y] | scalar-expression float-literal_11 ::= [0-9] float-literal_11 | [0-9] float-literal_12 ::= [0-9] float-literal_12 | [0-9] Llama.generate: prefix-match hit llama_print_timings: load time = 289.48 ms llama_print_timings: sample time = 1005.82 ms / 63 runs ( 15.97 ms per token, 62.64 tokens per second) llama_print_timings: prompt eval time = 0.00 ms / 1 tokens ( 0.00 ms per token, inf tokens per second) llama_print_timings: eval time = 872.28 ms / 63 runs ( 13.85 ms per token, 72.22 tokens per second) llama_print_timings: total time = 2021.73 msPrediction
andreasjansson/plasma:cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952IDnlmoezlb7fz5rcgryw2arhdtr4StatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
{}Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "andreasjansson/plasma:cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952", { input: {} } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run("andreasjansson/plasma:cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952") # The andreasjansson/plasma model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/andreasjansson/plasma/api#output-schema print(item, end="")To learn more, take a look at the guide on getting started with Python.
Run andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952", "input": {} }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
vec2 effect(vec2 p, float i, float time) { return vec2(sin(length(p.x * cos(time) - p.y * sin(time)) + time), cos(length(p.x * sin(time) + p.y * cos(time)) + time)); }{ "completed_at": "2023-12-06T15:42:05.514272Z", "created_at": "2023-12-06T15:42:02.692398Z", "data_removed": false, "error": null, "id": "nlmoezlb7fz5rcgryw2arhdtr4", "input": {}, "logs": "from_string grammar:\nroot ::= [v] [e] [c] [2] [ ] [e] [f] [f] [e] [c] [t] [(] [v] [e] [c] [2] [ ] [p] [,] [ ] [f] [l] [o] [a] [t] [ ] [i] [,] [ ] [f] [l] [o] [a] [t] [ ] [t] [i] [m] [e] [)] [ ] [{] [<U+000A>] [ ] [ ] return-statement [<U+000A>] [}]\nreturn-statement ::= [r] [e] [t] [u] [r] [n] [ ] vec2-expression [;]\nvec2-expression ::= single-vec2-expression | single-vec2-expression operation vec2-expression\nsingle-vec2-expression ::= [v] [e] [c] [2] [(] scalar-expression [,] [ ] scalar-expression [)]\noperation ::= [ ] [+] [ ] | [ ] [-] [ ] | [ ] [*] [ ] | [ ] [/] [ ]\nscalar-expression ::= single-scalar-expression | single-scalar-expression operation scalar-expression\nsingle-scalar-expression ::= float-literal | variable | math-func [(] math-arg [)]\nfloat-literal ::= float-literal_11 [.] float-literal_12 \nvariable ::= [p] [.] [x] | [p] [.] [y] | [i] | [t] [i] [m] [e]\nmath-func ::= [s] [i] [n] | [c] [o] [s] | [t] [a] [n] | [l] [e] [n] [g] [t] [h] | [s] [q] [r] [t] | [e] [x] [p]\nmath-arg ::= [p] [.] [x] | [p] [.] [y] | scalar-expression\nfloat-literal_11 ::= [0-9] float-literal_11 | [0-9] \nfloat-literal_12 ::= [0-9] float-literal_12 | [0-9] \nLlama.generate: prefix-match hit\nllama_print_timings: load time = 288.36 ms\nllama_print_timings: sample time = 1577.47 ms / 72 runs ( 21.91 ms per token, 45.64 tokens per second)\nllama_print_timings: prompt eval time = 0.00 ms / 1 tokens ( 0.00 ms per token, inf tokens per second)\nllama_print_timings: eval time = 1046.58 ms / 72 runs ( 14.54 ms per token, 68.80 tokens per second)\nllama_print_timings: total time = 2797.85 ms", "metrics": { "predict_time": 2.820014, "total_time": 2.821874 }, "output": [ "vec", "2", " effect", "(", "vec", "2", " p", ",", " float", " i", ",", " float", " time", ")", " {", "\n", " ", "return", " vec", "2", "(", "sin", "(", "length", "(", "p", ".", "x", " *", " cos", "(", "time", ")", " -", " p", ".", "y", " *", " sin", "(", "time", "))", " +", " time", "),", " cos", "(", "length", "(", "p", ".", "x", " *", " sin", "(", "time", ")", " +", " p", ".", "y", " *", " cos", "(", "time", "))", " +", " time", "));", "\n", "}" ], "started_at": "2023-12-06T15:42:02.694258Z", "status": "succeeded", "urls": { "stream": "https://streaming-api.svc.us.c.replicate.net/v1/predictions/nlmoezlb7fz5rcgryw2arhdtr4", "get": "https://api.replicate.com/v1/predictions/nlmoezlb7fz5rcgryw2arhdtr4", "cancel": "https://api.replicate.com/v1/predictions/nlmoezlb7fz5rcgryw2arhdtr4/cancel" }, "version": "cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952" }Generated infrom_string grammar: root ::= [v] [e] [c] [2] [ ] [e] [f] [f] [e] [c] [t] [(] [v] [e] [c] [2] [ ] [p] [,] [ ] [f] [l] [o] [a] [t] [ ] [i] [,] [ ] [f] [l] [o] [a] [t] [ ] [t] [i] [m] [e] [)] [ ] [{] [<U+000A>] [ ] [ ] return-statement [<U+000A>] [}] return-statement ::= [r] [e] [t] [u] [r] [n] [ ] vec2-expression [;] vec2-expression ::= single-vec2-expression | single-vec2-expression operation vec2-expression single-vec2-expression ::= [v] [e] [c] [2] [(] scalar-expression [,] [ ] scalar-expression [)] operation ::= [ ] [+] [ ] | [ ] [-] [ ] | [ ] [*] [ ] | [ ] [/] [ ] scalar-expression ::= single-scalar-expression | single-scalar-expression operation scalar-expression single-scalar-expression ::= float-literal | variable | math-func [(] math-arg [)] float-literal ::= float-literal_11 [.] float-literal_12 variable ::= [p] [.] [x] | [p] [.] [y] | [i] | [t] [i] [m] [e] math-func ::= [s] [i] [n] | [c] [o] [s] | [t] [a] [n] | [l] [e] [n] [g] [t] [h] | [s] [q] [r] [t] | [e] [x] [p] math-arg ::= [p] [.] [x] | [p] [.] [y] | scalar-expression float-literal_11 ::= [0-9] float-literal_11 | [0-9] float-literal_12 ::= [0-9] float-literal_12 | [0-9] Llama.generate: prefix-match hit llama_print_timings: load time = 288.36 ms llama_print_timings: sample time = 1577.47 ms / 72 runs ( 21.91 ms per token, 45.64 tokens per second) llama_print_timings: prompt eval time = 0.00 ms / 1 tokens ( 0.00 ms per token, inf tokens per second) llama_print_timings: eval time = 1046.58 ms / 72 runs ( 14.54 ms per token, 68.80 tokens per second) llama_print_timings: total time = 2797.85 msPrediction
andreasjansson/plasma:cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952IDrftcdylb6rjwmdmrmrado3pfluStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
{}Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "andreasjansson/plasma:cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952", { input: {} } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run("andreasjansson/plasma:cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952") # The andreasjansson/plasma model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/andreasjansson/plasma/api#output-schema print(item, end="")To learn more, take a look at the guide on getting started with Python.
Run andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952", "input": {} }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
vec2 effect(vec2 p, float i, float time) { return vec2(cos(i * length(p.x) * sin(length(p.y) * time)), sin(i * cos(length(p.x) * time))); }{ "completed_at": "2023-12-06T17:34:12.073102Z", "created_at": "2023-12-06T17:34:07.905362Z", "data_removed": false, "error": null, "id": "rftcdylb6rjwmdmrmrado3pflu", "input": {}, "logs": "from_string grammar:\nroot ::= [v] [e] [c] [2] [ ] [e] [f] [f] [e] [c] [t] [(] [v] [e] [c] [2] [ ] [p] [,] [ ] [f] [l] [o] [a] [t] [ ] [i] [,] [ ] [f] [l] [o] [a] [t] [ ] [t] [i] [m] [e] [)] [ ] [{] [<U+000A>] [ ] [ ] return-statement [<U+000A>] [}] \nreturn-statement ::= [r] [e] [t] [u] [r] [n] [ ] vec2-expression [;]\nvec2-expression ::= single-vec2-expression | single-vec2-expression operation vec2-expression\nsingle-vec2-expression ::= [v] [e] [c] [2] [(] scalar-expression [,] [ ] scalar-expression [)]\noperation ::= [ ] [+] [ ] | [ ] [-] [ ] | [ ] [*] [ ] | [ ] [/] [ ] \nscalar-expression ::= single-scalar-expression | single-scalar-expression operation scalar-expression \nsingle-scalar-expression ::= float-literal | variable | math-func [(] math-arg [)]\nfloat-literal ::= float-literal_11 [.] float-literal_12 \nvariable ::= [p] [.] [x] | [p] [.] [y] | [i] | [t] [i] [m] [e]\nmath-func ::= [s] [i] [n] | [c] [o] [s] | [t] [a] [n] | [l] [e] [n] [g] [t] [h] | [s] [q] [r] [t] | [e] [x] [p]\nmath-arg ::= [p] [.] [x] | [p] [.] [y] | scalar-expression\nfloat-literal_11 ::= [0-9] float-literal_11 | [0-9]\nfloat-literal_12 ::= [0-9] float-literal_12 | [0-9]\nLlama.generate: prefix-match hit\nllama_print_timings: load time = 392.68 ms\nllama_print_timings: sample time = 3012.74 ms / 61 runs ( 49.39 ms per token, 20.25 tokens per second)\nllama_print_timings: prompt eval time = 0.00 ms / 1 tokens ( 0.00 ms per token, inf tokens per second)\nllama_print_timings: eval time = 889.50 ms / 61 runs ( 14.58 ms per token, 68.58 tokens per second)\nllama_print_timings: total time = 4046.34 ms", "metrics": { "predict_time": 4.133799, "total_time": 4.16774 }, "output": [ "vec", "2", " effect", "(", "vec", "2", " p", ",", " float", " i", ",", " float", " time", ")", " {", "\n", " ", "return", " vec", "2", "(", "cos", "(", "i", " *", " length", "(", "p", ".", "x", ")", " *", " sin", "(", "length", "(", "p", ".", "y", ")", " *", " time", ")),", " sin", "(", "i", " *", " cos", "(", "length", "(", "p", ".", "x", ")", " *", " time", ")));", "\n", "}" ], "started_at": "2023-12-06T17:34:07.939303Z", "status": "succeeded", "urls": { "stream": "https://streaming-api.svc.us.c.replicate.net/v1/predictions/rftcdylb6rjwmdmrmrado3pflu", "get": "https://api.replicate.com/v1/predictions/rftcdylb6rjwmdmrmrado3pflu", "cancel": "https://api.replicate.com/v1/predictions/rftcdylb6rjwmdmrmrado3pflu/cancel" }, "version": "cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952" }Generated infrom_string grammar: root ::= [v] [e] [c] [2] [ ] [e] [f] [f] [e] [c] [t] [(] [v] [e] [c] [2] [ ] [p] [,] [ ] [f] [l] [o] [a] [t] [ ] [i] [,] [ ] [f] [l] [o] [a] [t] [ ] [t] [i] [m] [e] [)] [ ] [{] [<U+000A>] [ ] [ ] return-statement [<U+000A>] [}] return-statement ::= [r] [e] [t] [u] [r] [n] [ ] vec2-expression [;] vec2-expression ::= single-vec2-expression | single-vec2-expression operation vec2-expression single-vec2-expression ::= [v] [e] [c] [2] [(] scalar-expression [,] [ ] scalar-expression [)] operation ::= [ ] [+] [ ] | [ ] [-] [ ] | [ ] [*] [ ] | [ ] [/] [ ] scalar-expression ::= single-scalar-expression | single-scalar-expression operation scalar-expression single-scalar-expression ::= float-literal | variable | math-func [(] math-arg [)] float-literal ::= float-literal_11 [.] float-literal_12 variable ::= [p] [.] [x] | [p] [.] [y] | [i] | [t] [i] [m] [e] math-func ::= [s] [i] [n] | [c] [o] [s] | [t] [a] [n] | [l] [e] [n] [g] [t] [h] | [s] [q] [r] [t] | [e] [x] [p] math-arg ::= [p] [.] [x] | [p] [.] [y] | scalar-expression float-literal_11 ::= [0-9] float-literal_11 | [0-9] float-literal_12 ::= [0-9] float-literal_12 | [0-9] Llama.generate: prefix-match hit llama_print_timings: load time = 392.68 ms llama_print_timings: sample time = 3012.74 ms / 61 runs ( 49.39 ms per token, 20.25 tokens per second) llama_print_timings: prompt eval time = 0.00 ms / 1 tokens ( 0.00 ms per token, inf tokens per second) llama_print_timings: eval time = 889.50 ms / 61 runs ( 14.58 ms per token, 68.58 tokens per second) llama_print_timings: total time = 4046.34 msPrediction
andreasjansson/plasma:cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952IDjji3fr3bucnr3mq7dsad6iwldiStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
{}Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "andreasjansson/plasma:cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952", { input: {} } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run("andreasjansson/plasma:cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952") # The andreasjansson/plasma model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/andreasjansson/plasma/api#output-schema print(item, end="")To learn more, take a look at the guide on getting started with Python.
Run andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952", "input": {} }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
vec2 effect(vec2 p, float i, float time) { return vec2(sin(length(p.x) * length(p.y) * i + time), cos(length(p.x) * length(p.y) * i - time)); }{ "completed_at": "2023-12-07T12:13:29.745194Z", "created_at": "2023-12-07T12:13:25.057641Z", "data_removed": false, "error": null, "id": "jji3fr3bucnr3mq7dsad6iwldi", "input": {}, "logs": "from_string grammar:\nroot ::= [v] [e] [c] [2] [ ] [e] [f] [f] [e] [c] [t] [(] [v] [e] [c] [2] [ ] [p] [,] [ ] [f] [l] [o] [a] [t] [ ] [i] [,] [ ] [f] [l] [o] [a] [t] [ ] [t] [i] [m] [e] [)] [ ] [{] [<U+000A>] [ ] [ ] return-statement [<U+000A>] [}] \nreturn-statement ::= [r] [e] [t] [u] [r] [n] [ ] vec2-expression [;]\nvec2-expression ::= single-vec2-expression | single-vec2-expression operation vec2-expression\nsingle-vec2-expression ::= [v] [e] [c] [2] [(] scalar-expression [,] [ ] scalar-expression [)]\noperation ::= [ ] [+] [ ] | [ ] [-] [ ] | [ ] [*] [ ] | [ ] [/] [ ]\nscalar-expression ::= single-scalar-expression | single-scalar-expression operation scalar-expression\nsingle-scalar-expression ::= float-literal | variable | math-func [(] math-arg [)]\nfloat-literal ::= float-literal_11 [.] float-literal_12\nvariable ::= [p] [.] [x] | [p] [.] [y] | [i] | [t] [i] [m] [e]\nmath-func ::= [s] [i] [n] | [c] [o] [s] | [t] [a] [n] | [l] [e] [n] [g] [t] [h] | [s] [q] [r] [t] | [e] [x] [p]\nmath-arg ::= [p] [.] [x] | [p] [.] [y] | scalar-expression \nfloat-literal_11 ::= [0-9] float-literal_11 | [0-9]\nfloat-literal_12 ::= [0-9] float-literal_12 | [0-9]\nLlama.generate: prefix-match hit\nllama_print_timings: load time = 314.60 ms\nllama_print_timings: sample time = 3573.61 ms / 64 runs ( 55.84 ms per token, 17.91 tokens per second)\nllama_print_timings: prompt eval time = 0.00 ms / 1 tokens ( 0.00 ms per token, inf tokens per second)\nllama_print_timings: eval time = 938.93 ms / 64 runs ( 14.67 ms per token, 68.16 tokens per second)\nllama_print_timings: total time = 4668.46 ms", "metrics": { "predict_time": 4.680982, "total_time": 4.687553 }, "output": [ "vec", "2", " effect", "(", "vec", "2", " p", ",", " float", " i", ",", " float", " time", ")", " {", "\n", " ", "return", " vec", "2", "(", "sin", "(", "length", "(", "p", ".", "x", ")", " *", " length", "(", "p", ".", "y", ")", " *", " i", " +", " time", "),", " cos", "(", "length", "(", "p", ".", "x", ")", " *", " length", "(", "p", ".", "y", ")", " *", " i", " -", " time", "));", "\n", "}" ], "started_at": "2023-12-07T12:13:25.064212Z", "status": "succeeded", "urls": { "stream": "https://streaming-api.svc.us.c.replicate.net/v1/predictions/jji3fr3bucnr3mq7dsad6iwldi", "get": "https://api.replicate.com/v1/predictions/jji3fr3bucnr3mq7dsad6iwldi", "cancel": "https://api.replicate.com/v1/predictions/jji3fr3bucnr3mq7dsad6iwldi/cancel" }, "version": "cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952" }Generated infrom_string grammar: root ::= [v] [e] [c] [2] [ ] [e] [f] [f] [e] [c] [t] [(] [v] [e] [c] [2] [ ] [p] [,] [ ] [f] [l] [o] [a] [t] [ ] [i] [,] [ ] [f] [l] [o] [a] [t] [ ] [t] [i] [m] [e] [)] [ ] [{] [<U+000A>] [ ] [ ] return-statement [<U+000A>] [}] return-statement ::= [r] [e] [t] [u] [r] [n] [ ] vec2-expression [;] vec2-expression ::= single-vec2-expression | single-vec2-expression operation vec2-expression single-vec2-expression ::= [v] [e] [c] [2] [(] scalar-expression [,] [ ] scalar-expression [)] operation ::= [ ] [+] [ ] | [ ] [-] [ ] | [ ] [*] [ ] | [ ] [/] [ ] scalar-expression ::= single-scalar-expression | single-scalar-expression operation scalar-expression single-scalar-expression ::= float-literal | variable | math-func [(] math-arg [)] float-literal ::= float-literal_11 [.] float-literal_12 variable ::= [p] [.] [x] | [p] [.] [y] | [i] | [t] [i] [m] [e] math-func ::= [s] [i] [n] | [c] [o] [s] | [t] [a] [n] | [l] [e] [n] [g] [t] [h] | [s] [q] [r] [t] | [e] [x] [p] math-arg ::= [p] [.] [x] | [p] [.] [y] | scalar-expression float-literal_11 ::= [0-9] float-literal_11 | [0-9] float-literal_12 ::= [0-9] float-literal_12 | [0-9] Llama.generate: prefix-match hit llama_print_timings: load time = 314.60 ms llama_print_timings: sample time = 3573.61 ms / 64 runs ( 55.84 ms per token, 17.91 tokens per second) llama_print_timings: prompt eval time = 0.00 ms / 1 tokens ( 0.00 ms per token, inf tokens per second) llama_print_timings: eval time = 938.93 ms / 64 runs ( 14.67 ms per token, 68.16 tokens per second) llama_print_timings: total time = 4668.46 msPrediction
andreasjansson/plasma:cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952IDpckh7h3bgytxgkkzdkm5ngrh6qStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
{}Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "andreasjansson/plasma:cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952", { input: {} } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run("andreasjansson/plasma:cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952") # The andreasjansson/plasma model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/andreasjansson/plasma/api#output-schema print(item, end="")To learn more, take a look at the guide on getting started with Python.
Run andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952", "input": {} }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
vec2 effect(vec2 p, float i, float time) { return vec2(sin(p.x * i * 1.5 + time), cos(p.y * i * 0.8 + time)) * vec2(cos(length(p.y * i + time)), sin(length(p.y * i - time))) / vec2(1.0, i); }{ "completed_at": "2023-12-06T11:38:22.988259Z", "created_at": "2023-12-06T11:38:19.849270Z", "data_removed": false, "error": null, "id": "pckh7h3bgytxgkkzdkm5ngrh6q", "input": {}, "logs": "from_string grammar:\nroot ::= [v] [e] [c] [2] [ ] [e] [f] [f] [e] [c] [t] [(] [v] [e] [c] [2] [ ] [p] [,] [ ] [f] [l] [o] [a] [t] [ ] [i] [,] [ ] [f] [l] [o] [a] [t] [ ] [t] [i] [m] [e] [)] [ ] [{] [<U+000A>] [ ] [ ] return-statement [<U+000A>] [}] \nreturn-statement ::= [r] [e] [t] [u] [r] [n] [ ] vec2-expression [;]\nvec2-expression ::= single-vec2-expression | single-vec2-expression operation vec2-expression\nsingle-vec2-expression ::= [v] [e] [c] [2] [(] scalar-expression [,] [ ] scalar-expression [)]\noperation ::= [ ] [+] [ ] | [ ] [-] [ ] | [ ] [*] [ ] | [ ] [/] [ ]\nscalar-expression ::= single-scalar-expression | single-scalar-expression operation scalar-expression\nsingle-scalar-expression ::= float-literal | variable | math-func [(] math-arg [)]\nfloat-literal ::= float-literal_11 [.] float-literal_12 \nvariable ::= [p] [.] [x] | [p] [.] [y] | [i] | [t] [i] [m] [e]\nmath-func ::= [s] [i] [n] | [c] [o] [s] | [t] [a] [n] | [l] [e] [n] [g] [t] [h] | [s] [q] [r] [t] | [e] [x] [p]\nmath-arg ::= [p] [.] [x] | [p] [.] [y] | scalar-expression\nfloat-literal_11 ::= [0-9] float-literal_11 | [0-9]\nfloat-literal_12 ::= [0-9] float-literal_12 | [0-9]\nLlama.generate: prefix-match hit\nllama_print_timings: load time = 340.52 ms\nllama_print_timings: sample time = 1484.09 ms / 93 runs ( 15.96 ms per token, 62.66 tokens per second)\nllama_print_timings: prompt eval time = 0.00 ms / 1 tokens ( 0.00 ms per token, inf tokens per second)\nllama_print_timings: eval time = 1349.97 ms / 93 runs ( 14.52 ms per token, 68.89 tokens per second)\nllama_print_timings: total time = 3046.91 ms", "metrics": { "predict_time": 3.097387, "total_time": 3.138989 }, "output": [ "vec", "2", " effect", "(", "vec", "2", " p", ",", " float", " i", ",", " float", " time", ")", " {", "\n", " ", " return", " vec", "2", "(", "sin", "(", "p", ".", "x", " *", " i", " *", " ", "1", ".", "5", " +", " time", "),", " cos", "(", "p", ".", "y", " *", " i", " *", " ", "0", ".", "8", " +", " time", "))", " *", " vec", "2", "(", "cos", "(", "length", "(", "p", ".", "y", " *", " i", " +", " time", ")),", " sin", "(", "length", "(", "p", ".", "y", " *", " i", " -", " time", ")))", " /", " ", "vec", "2", "(", "1", ".", "0", ",", " i", ");", "\n", "}" ], "started_at": "2023-12-06T11:38:19.890872Z", "status": "succeeded", "urls": { "stream": "https://streaming-api.svc.us.c.replicate.net/v1/predictions/pckh7h3bgytxgkkzdkm5ngrh6q", "get": "https://api.replicate.com/v1/predictions/pckh7h3bgytxgkkzdkm5ngrh6q", "cancel": "https://api.replicate.com/v1/predictions/pckh7h3bgytxgkkzdkm5ngrh6q/cancel" }, "version": "cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952" }Generated infrom_string grammar: root ::= [v] [e] [c] [2] [ ] [e] [f] [f] [e] [c] [t] [(] [v] [e] [c] [2] [ ] [p] [,] [ ] [f] [l] [o] [a] [t] [ ] [i] [,] [ ] [f] [l] [o] [a] [t] [ ] [t] [i] [m] [e] [)] [ ] [{] [<U+000A>] [ ] [ ] return-statement [<U+000A>] [}] return-statement ::= [r] [e] [t] [u] [r] [n] [ ] vec2-expression [;] vec2-expression ::= single-vec2-expression | single-vec2-expression operation vec2-expression single-vec2-expression ::= [v] [e] [c] [2] [(] scalar-expression [,] [ ] scalar-expression [)] operation ::= [ ] [+] [ ] | [ ] [-] [ ] | [ ] [*] [ ] | [ ] [/] [ ] scalar-expression ::= single-scalar-expression | single-scalar-expression operation scalar-expression single-scalar-expression ::= float-literal | variable | math-func [(] math-arg [)] float-literal ::= float-literal_11 [.] float-literal_12 variable ::= [p] [.] [x] | [p] [.] [y] | [i] | [t] [i] [m] [e] math-func ::= [s] [i] [n] | [c] [o] [s] | [t] [a] [n] | [l] [e] [n] [g] [t] [h] | [s] [q] [r] [t] | [e] [x] [p] math-arg ::= [p] [.] [x] | [p] [.] [y] | scalar-expression float-literal_11 ::= [0-9] float-literal_11 | [0-9] float-literal_12 ::= [0-9] float-literal_12 | [0-9] Llama.generate: prefix-match hit llama_print_timings: load time = 340.52 ms llama_print_timings: sample time = 1484.09 ms / 93 runs ( 15.96 ms per token, 62.66 tokens per second) llama_print_timings: prompt eval time = 0.00 ms / 1 tokens ( 0.00 ms per token, inf tokens per second) llama_print_timings: eval time = 1349.97 ms / 93 runs ( 14.52 ms per token, 68.89 tokens per second) llama_print_timings: total time = 3046.91 msPrediction
andreasjansson/plasma:cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952IDobok5x3bcoshf3rtjbkyuelljyStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
{}Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "andreasjansson/plasma:cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952", { input: {} } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run("andreasjansson/plasma:cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952") # The andreasjansson/plasma model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/andreasjansson/plasma/api#output-schema print(item, end="")To learn more, take a look at the guide on getting started with Python.
Run andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952", "input": {} }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
vec2 effect(vec2 p, float i, float time) { return vec2(sin(length(p.x * 1.5 + sin(time)) + length(p.y * 2.0 + cos(time))), cos(length(p.x * 0.75 + sin(time)) + length(p.y * 1.25 + cos(time)))) / vec2(sin(time), cos(time)); }{ "completed_at": "2023-12-06T12:46:49.467875Z", "created_at": "2023-12-06T12:46:45.272557Z", "data_removed": false, "error": null, "id": "obok5x3bcoshf3rtjbkyuelljy", "input": {}, "logs": "from_string grammar:\nroot ::= [v] [e] [c] [2] [ ] [e] [f] [f] [e] [c] [t] [(] [v] [e] [c] [2] [ ] [p] [,] [ ] [f] [l] [o] [a] [t] [ ] [i] [,] [ ] [f] [l] [o] [a] [t] [ ] [t] [i] [m] [e] [)] [ ] [{] [<U+000A>] [ ] [ ] return-statement [<U+000A>] [}]\nreturn-statement ::= [r] [e] [t] [u] [r] [n] [ ] vec2-expression [;]\nvec2-expression ::= single-vec2-expression | single-vec2-expression operation vec2-expression\nsingle-vec2-expression ::= [v] [e] [c] [2] [(] scalar-expression [,] [ ] scalar-expression [)]\noperation ::= [ ] [+] [ ] | [ ] [-] [ ] | [ ] [*] [ ] | [ ] [/] [ ]\nscalar-expression ::= single-scalar-expression | single-scalar-expression operation scalar-expression\nsingle-scalar-expression ::= float-literal | variable | math-func [(] math-arg [)]\nfloat-literal ::= float-literal_11 [.] float-literal_12\nvariable ::= [p] [.] [x] | [p] [.] [y] | [i] | [t] [i] [m] [e]\nmath-func ::= [s] [i] [n] | [c] [o] [s] | [t] [a] [n] | [l] [e] [n] [g] [t] [h] | [s] [q] [r] [t] | [e] [x] [p] \nmath-arg ::= [p] [.] [x] | [p] [.] [y] | scalar-expression\nfloat-literal_11 ::= [0-9] float-literal_11 | [0-9]\nfloat-literal_12 ::= [0-9] float-literal_12 | [0-9]\nLlama.generate: prefix-match hit\nllama_print_timings: load time = 295.26 ms\nllama_print_timings: sample time = 2324.13 ms / 107 runs ( 21.72 ms per token, 46.04 tokens per second)\nllama_print_timings: prompt eval time = 0.00 ms / 1 tokens ( 0.00 ms per token, inf tokens per second)\nllama_print_timings: eval time = 1553.23 ms / 107 runs ( 14.52 ms per token, 68.89 tokens per second)\nllama_print_timings: total time = 4123.81 ms", "metrics": { "predict_time": 4.160307, "total_time": 4.195318 }, "output": [ "v", "ec", "2", " effect", "(", "vec", "2", " p", ",", " float", " i", ",", " float", " time", ")", " {", "\n", " ", " return", " vec", "2", "(", "sin", "(", "length", "(", "p", ".", "x", " *", " ", "1", ".", "5", " +", " sin", "(", "time", "))", " +", " length", "(", "p", ".", "y", " *", " ", "2", ".", "0", " +", " cos", "(", "time", "))", "),", " cos", "(", "length", "(", "p", ".", "x", " *", " ", "0", ".", "7", "5", " +", " sin", "(", "time", "))", " +", " length", "(", "p", ".", "y", " *", " ", "1", ".", "2", "5", " +", " cos", "(", "time", "))))", " /", " ", "vec", "2", "(", "sin", "(", "time", "),", " cos", "(", "time", "));", "\n", "}" ], "started_at": "2023-12-06T12:46:45.307568Z", "status": "succeeded", "urls": { "stream": "https://streaming-api.svc.us.c.replicate.net/v1/predictions/obok5x3bcoshf3rtjbkyuelljy", "get": "https://api.replicate.com/v1/predictions/obok5x3bcoshf3rtjbkyuelljy", "cancel": "https://api.replicate.com/v1/predictions/obok5x3bcoshf3rtjbkyuelljy/cancel" }, "version": "cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952" }Generated infrom_string grammar: root ::= [v] [e] [c] [2] [ ] [e] [f] [f] [e] [c] [t] [(] [v] [e] [c] [2] [ ] [p] [,] [ ] [f] [l] [o] [a] [t] [ ] [i] [,] [ ] [f] [l] [o] [a] [t] [ ] [t] [i] [m] [e] [)] [ ] [{] [<U+000A>] [ ] [ ] return-statement [<U+000A>] [}] return-statement ::= [r] [e] [t] [u] [r] [n] [ ] vec2-expression [;] vec2-expression ::= single-vec2-expression | single-vec2-expression operation vec2-expression single-vec2-expression ::= [v] [e] [c] [2] [(] scalar-expression [,] [ ] scalar-expression [)] operation ::= [ ] [+] [ ] | [ ] [-] [ ] | [ ] [*] [ ] | [ ] [/] [ ] scalar-expression ::= single-scalar-expression | single-scalar-expression operation scalar-expression single-scalar-expression ::= float-literal | variable | math-func [(] math-arg [)] float-literal ::= float-literal_11 [.] float-literal_12 variable ::= [p] [.] [x] | [p] [.] [y] | [i] | [t] [i] [m] [e] math-func ::= [s] [i] [n] | [c] [o] [s] | [t] [a] [n] | [l] [e] [n] [g] [t] [h] | [s] [q] [r] [t] | [e] [x] [p] math-arg ::= [p] [.] [x] | [p] [.] [y] | scalar-expression float-literal_11 ::= [0-9] float-literal_11 | [0-9] float-literal_12 ::= [0-9] float-literal_12 | [0-9] Llama.generate: prefix-match hit llama_print_timings: load time = 295.26 ms llama_print_timings: sample time = 2324.13 ms / 107 runs ( 21.72 ms per token, 46.04 tokens per second) llama_print_timings: prompt eval time = 0.00 ms / 1 tokens ( 0.00 ms per token, inf tokens per second) llama_print_timings: eval time = 1553.23 ms / 107 runs ( 14.52 ms per token, 68.89 tokens per second) llama_print_timings: total time = 4123.81 msPrediction
andreasjansson/plasma:cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952IDg7vaaktbxkjkl6zddxvglstmmmStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
{}Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "andreasjansson/plasma:cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952", { input: {} } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run("andreasjansson/plasma:cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952") # The andreasjansson/plasma model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/andreasjansson/plasma/api#output-schema print(item, end="")To learn more, take a look at the guide on getting started with Python.
Run andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952", "input": {} }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
vec2 effect(vec2 p, float i, float time) { return vec2(sin(length(p.x - p.y) * i * 5.0 + time), cos(length(p.x + p.y) * i * 3.0 + time)); }{ "completed_at": "2023-12-06T18:11:26.538956Z", "created_at": "2023-12-06T18:11:24.248022Z", "data_removed": false, "error": null, "id": "g7vaaktbxkjkl6zddxvglstmmm", "input": {}, "logs": "from_string grammar:\nroot ::= [v] [e] [c] [2] [ ] [e] [f] [f] [e] [c] [t] [(] [v] [e] [c] [2] [ ] [p] [,] [ ] [f] [l] [o] [a] [t] [ ] [i] [,] [ ] [f] [l] [o] [a] [t] [ ] [t] [i] [m] [e] [)] [ ] [{] [<U+000A>] [ ] [ ] return-statement [<U+000A>] [}]\nreturn-statement ::= [r] [e] [t] [u] [r] [n] [ ] vec2-expression [;]\nvec2-expression ::= single-vec2-expression | single-vec2-expression operation vec2-expression\nsingle-vec2-expression ::= [v] [e] [c] [2] [(] scalar-expression [,] [ ] scalar-expression [)]\noperation ::= [ ] [+] [ ] | [ ] [-] [ ] | [ ] [*] [ ] | [ ] [/] [ ] \nscalar-expression ::= single-scalar-expression | single-scalar-expression operation scalar-expression \nsingle-scalar-expression ::= float-literal | variable | math-func [(] math-arg [)] \nfloat-literal ::= float-literal_11 [.] float-literal_12\nvariable ::= [p] [.] [x] | [p] [.] [y] | [i] | [t] [i] [m] [e]\nmath-func ::= [s] [i] [n] | [c] [o] [s] | [t] [a] [n] | [l] [e] [n] [g] [t] [h] | [s] [q] [r] [t] | [e] [x] [p]\nmath-arg ::= [p] [.] [x] | [p] [.] [y] | scalar-expression\nfloat-literal_11 ::= [0-9] float-literal_11 | [0-9]\nfloat-literal_12 ::= [0-9] float-literal_12 | [0-9]\nLlama.generate: prefix-match hit\nllama_print_timings: load time = 289.32 ms\nllama_print_timings: sample time = 1033.77 ms / 69 runs ( 14.98 ms per token, 66.75 tokens per second)\nllama_print_timings: prompt eval time = 0.00 ms / 1 tokens ( 0.00 ms per token, inf tokens per second)\nllama_print_timings: eval time = 998.63 ms / 69 runs ( 14.47 ms per token, 69.09 tokens per second)\nllama_print_timings: total time = 2190.30 ms", "metrics": { "predict_time": 2.23984, "total_time": 2.290934 }, "output": [ "v", "ec", "2", " effect", "(", "vec", "2", " p", ",", " float", " i", ",", " float", " time", ")", " {", "\n", " ", "return", " vec", "2", "(", "sin", "(", "length", "(", "p", ".", "x", " -", " p", ".", "y", ")", " *", " i", " *", " ", "5", ".", "0", " +", " time", "),", " cos", "(", "length", "(", "p", ".", "x", " +", " p", ".", "y", ")", " *", " i", " *", " ", "3", ".", "0", " +", " time", "));", "\n", "}" ], "started_at": "2023-12-06T18:11:24.299116Z", "status": "succeeded", "urls": { "stream": "https://streaming-api.svc.us.c.replicate.net/v1/predictions/g7vaaktbxkjkl6zddxvglstmmm", "get": "https://api.replicate.com/v1/predictions/g7vaaktbxkjkl6zddxvglstmmm", "cancel": "https://api.replicate.com/v1/predictions/g7vaaktbxkjkl6zddxvglstmmm/cancel" }, "version": "cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952" }Generated infrom_string grammar: root ::= [v] [e] [c] [2] [ ] [e] [f] [f] [e] [c] [t] [(] [v] [e] [c] [2] [ ] [p] [,] [ ] [f] [l] [o] [a] [t] [ ] [i] [,] [ ] [f] [l] [o] [a] [t] [ ] [t] [i] [m] [e] [)] [ ] [{] [<U+000A>] [ ] [ ] return-statement [<U+000A>] [}] return-statement ::= [r] [e] [t] [u] [r] [n] [ ] vec2-expression [;] vec2-expression ::= single-vec2-expression | single-vec2-expression operation vec2-expression single-vec2-expression ::= [v] [e] [c] [2] [(] scalar-expression [,] [ ] scalar-expression [)] operation ::= [ ] [+] [ ] | [ ] [-] [ ] | [ ] [*] [ ] | [ ] [/] [ ] scalar-expression ::= single-scalar-expression | single-scalar-expression operation scalar-expression single-scalar-expression ::= float-literal | variable | math-func [(] math-arg [)] float-literal ::= float-literal_11 [.] float-literal_12 variable ::= [p] [.] [x] | [p] [.] [y] | [i] | [t] [i] [m] [e] math-func ::= [s] [i] [n] | [c] [o] [s] | [t] [a] [n] | [l] [e] [n] [g] [t] [h] | [s] [q] [r] [t] | [e] [x] [p] math-arg ::= [p] [.] [x] | [p] [.] [y] | scalar-expression float-literal_11 ::= [0-9] float-literal_11 | [0-9] float-literal_12 ::= [0-9] float-literal_12 | [0-9] Llama.generate: prefix-match hit llama_print_timings: load time = 289.32 ms llama_print_timings: sample time = 1033.77 ms / 69 runs ( 14.98 ms per token, 66.75 tokens per second) llama_print_timings: prompt eval time = 0.00 ms / 1 tokens ( 0.00 ms per token, inf tokens per second) llama_print_timings: eval time = 998.63 ms / 69 runs ( 14.47 ms per token, 69.09 tokens per second) llama_print_timings: total time = 2190.30 msPrediction
andreasjansson/plasma:cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952IDmrxue7lblaa3s4gvweowg6nvsyStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
{}Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "andreasjansson/plasma:cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952", { input: {} } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run("andreasjansson/plasma:cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952") # The andreasjansson/plasma model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/andreasjansson/plasma/api#output-schema print(item, end="")To learn more, take a look at the guide on getting started with Python.
Run andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952", "input": {} }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
vec2 effect(vec2 p, float i, float time) { return vec2(sin(length(p.y) * i + time), cos(length(p.x) * i + time)) / vec2(i, i); }{ "completed_at": "2023-12-06T12:48:50.605657Z", "created_at": "2023-12-06T12:48:48.484099Z", "data_removed": false, "error": null, "id": "mrxue7lblaa3s4gvweowg6nvsy", "input": {}, "logs": "from_string grammar:\nroot ::= [v] [e] [c] [2] [ ] [e] [f] [f] [e] [c] [t] [(] [v] [e] [c] [2] [ ] [p] [,] [ ] [f] [l] [o] [a] [t] [ ] [i] [,] [ ] [f] [l] [o] [a] [t] [ ] [t] [i] [m] [e] [)] [ ] [{] [<U+000A>] [ ] [ ] return-statement [<U+000A>] [}]\nreturn-statement ::= [r] [e] [t] [u] [r] [n] [ ] vec2-expression [;]\nvec2-expression ::= single-vec2-expression | single-vec2-expression operation vec2-expression\nsingle-vec2-expression ::= [v] [e] [c] [2] [(] scalar-expression [,] [ ] scalar-expression [)]\noperation ::= [ ] [+] [ ] | [ ] [-] [ ] | [ ] [*] [ ] | [ ] [/] [ ]\nscalar-expression ::= single-scalar-expression | single-scalar-expression operation scalar-expression\nsingle-scalar-expression ::= float-literal | variable | math-func [(] math-arg [)]\nfloat-literal ::= float-literal_11 [.] float-literal_12 \nvariable ::= [p] [.] [x] | [p] [.] [y] | [i] | [t] [i] [m] [e]\nmath-func ::= [s] [i] [n] | [c] [o] [s] | [t] [a] [n] | [l] [e] [n] [g] [t] [h] | [s] [q] [r] [t] | [e] [x] [p]\nmath-arg ::= [p] [.] [x] | [p] [.] [y] | scalar-expression\nfloat-literal_11 ::= [0-9] float-literal_11 | [0-9] \nfloat-literal_12 ::= [0-9] float-literal_12 | [0-9]\nLlama.generate: prefix-match hit\nllama_print_timings: load time = 295.26 ms\nllama_print_timings: sample time = 1058.48 ms / 60 runs ( 17.64 ms per token, 56.68 tokens per second)\nllama_print_timings: prompt eval time = 0.00 ms / 1 tokens ( 0.00 ms per token, inf tokens per second)\nllama_print_timings: eval time = 866.57 ms / 60 runs ( 14.44 ms per token, 69.24 tokens per second)\nllama_print_timings: total time = 2064.12 ms", "metrics": { "predict_time": 2.091401, "total_time": 2.121558 }, "output": [ "v", "ec", "2", " effect", "(", "vec", "2", " p", ",", " float", " i", ",", " float", " time", ")", " {", "\n", " ", "return", " vec", "2", "(", "sin", "(", "length", "(", "p", ".", "y", ")", " *", " i", " +", " time", "),", " cos", "(", "length", "(", "p", ".", "x", ")", " *", " i", " +", " time", "))", " /", " ", "vec", "2", "(", "i", ",", " i", ");", "\n", "}" ], "started_at": "2023-12-06T12:48:48.514256Z", "status": "succeeded", "urls": { "stream": "https://streaming-api.svc.us.c.replicate.net/v1/predictions/mrxue7lblaa3s4gvweowg6nvsy", "get": "https://api.replicate.com/v1/predictions/mrxue7lblaa3s4gvweowg6nvsy", "cancel": "https://api.replicate.com/v1/predictions/mrxue7lblaa3s4gvweowg6nvsy/cancel" }, "version": "cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952" }Generated infrom_string grammar: root ::= [v] [e] [c] [2] [ ] [e] [f] [f] [e] [c] [t] [(] [v] [e] [c] [2] [ ] [p] [,] [ ] [f] [l] [o] [a] [t] [ ] [i] [,] [ ] [f] [l] [o] [a] [t] [ ] [t] [i] [m] [e] [)] [ ] [{] [<U+000A>] [ ] [ ] return-statement [<U+000A>] [}] return-statement ::= [r] [e] [t] [u] [r] [n] [ ] vec2-expression [;] vec2-expression ::= single-vec2-expression | single-vec2-expression operation vec2-expression single-vec2-expression ::= [v] [e] [c] [2] [(] scalar-expression [,] [ ] scalar-expression [)] operation ::= [ ] [+] [ ] | [ ] [-] [ ] | [ ] [*] [ ] | [ ] [/] [ ] scalar-expression ::= single-scalar-expression | single-scalar-expression operation scalar-expression single-scalar-expression ::= float-literal | variable | math-func [(] math-arg [)] float-literal ::= float-literal_11 [.] float-literal_12 variable ::= [p] [.] [x] | [p] [.] [y] | [i] | [t] [i] [m] [e] math-func ::= [s] [i] [n] | [c] [o] [s] | [t] [a] [n] | [l] [e] [n] [g] [t] [h] | [s] [q] [r] [t] | [e] [x] [p] math-arg ::= [p] [.] [x] | [p] [.] [y] | scalar-expression float-literal_11 ::= [0-9] float-literal_11 | [0-9] float-literal_12 ::= [0-9] float-literal_12 | [0-9] Llama.generate: prefix-match hit llama_print_timings: load time = 295.26 ms llama_print_timings: sample time = 1058.48 ms / 60 runs ( 17.64 ms per token, 56.68 tokens per second) llama_print_timings: prompt eval time = 0.00 ms / 1 tokens ( 0.00 ms per token, inf tokens per second) llama_print_timings: eval time = 866.57 ms / 60 runs ( 14.44 ms per token, 69.24 tokens per second) llama_print_timings: total time = 2064.12 msPrediction
andreasjansson/plasma:c0386a8ad96fea983e507fd410f9f93450c063f6e98cdc3fdd64684b8e343032IDgcqxuulbl7fzat7667gsojyrhuStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
{}Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "andreasjansson/plasma:c0386a8ad96fea983e507fd410f9f93450c063f6e98cdc3fdd64684b8e343032", { input: {} } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run("andreasjansson/plasma:c0386a8ad96fea983e507fd410f9f93450c063f6e98cdc3fdd64684b8e343032") # The andreasjansson/plasma model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/andreasjansson/plasma/api#output-schema print(item, end="")To learn more, take a look at the guide on getting started with Python.
Run andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "c0386a8ad96fea983e507fd410f9f93450c063f6e98cdc3fdd64684b8e343032", "input": {} }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
vec2 effect(vec2 p, float i, float time) { return vec2(cos(p.x * i + time), sin(p.y * i + time)) * vec2(sin(length(p.x + p.y) + time), cos(length(p.x - p.y) + time)) / vec2(i, 1.0); }{ "completed_at": "2023-12-05T14:22:57.361321Z", "created_at": "2023-12-05T14:22:54.587189Z", "data_removed": false, "error": null, "id": "gcqxuulbl7fzat7667gsojyrhu", "input": {}, "logs": "from_string grammar:\nroot ::= [v] [e] [c] [2] [ ] [e] [f] [f] [e] [c] [t] [(] [v] [e] [c] [2] [ ] [p] [,] [ ] [f] [l] [o] [a] [t] [ ] [i] [,] [ ] [f] [l] [o] [a] [t] [ ] [t] [i] [m] [e] [)] [ ] [{] [<U+000A>] [ ] [ ] return-statement [<U+000A>] [}]\nreturn-statement ::= [r] [e] [t] [u] [r] [n] [ ] vec2-expression [;]\nvec2-expression ::= single-vec2-expression | single-vec2-expression operation vec2-expression\nsingle-vec2-expression ::= [v] [e] [c] [2] [(] scalar-expression [,] [ ] scalar-expression [)]\noperation ::= [ ] [+] [ ] | [ ] [-] [ ] | [ ] [*] [ ] | [ ] [/] []\nscalar-expression ::= single-scalar-expression | single-scalar-expression operation scalar-expression\nsingle-scalar-expression ::= float-literal | variable | math-func [(] math-arg [)]\nfloat-literal ::= float-literal_11 [.] float-literal_12\nvariable ::= [p] [.] [x] | [p] [.] [y] | [i] | [t] [i] [m] [e] \nmath-func ::= [s] [i] [n] | [c] [o] [s] | [t] [a] [n] | [l] [e] [n] [g] [t] [h] | [s] [q] [r] [t] | [e] [x] [p] \nmath-arg ::= [p] [.] [x] | [p] [.] [y] | scalar-expression\nfloat-literal_11 ::= [0-9] float-literal_11 | [0-9]\nfloat-literal_12 ::= [0-9] float-literal_12 | [0-9]\nLlama.generate: prefix-match hit\nllama_print_timings: load time = 289.74 ms\nllama_print_timings: sample time = 1264.81 ms / 91 runs ( 13.90 ms per token, 71.95 tokens per second)\nllama_print_timings: prompt eval time = 0.00 ms / 1 tokens ( 0.00 ms per token, inf tokens per second)\nllama_print_timings: eval time = 1267.31 ms / 91 runs ( 13.93 ms per token, 71.81 tokens per second)\nllama_print_timings: total time = 2749.96 ms", "metrics": { "predict_time": 2.769513, "total_time": 2.774132 }, "output": [ "v", "ec", "2", " effect", "(", "vec", "2", " p", ",", " float", " i", ",", " float", " time", ")", " {", "\n", " ", "return", " vec", "2", "(", "cos", "(", "p", ".", "x", " *", " i", " +", " time", "),", " sin", "(", "p", ".", "y", " *", " i", " +", " time", "))", " *", " vec", "2", "(", "sin", "(", "length", "(", "p", ".", "x", " +", " p", ".", "y", ")", " +", " time", "),", " cos", "(", "length", "(", "p", ".", "x", " -", " p", ".", "y", ")", " +", " time", "))", " /", " ", "vec", "2", "(", "i", ",", " ", "1", ".", "0", ");", "\n", "}" ], "started_at": "2023-12-05T14:22:54.591808Z", "status": "succeeded", "urls": { "stream": "https://streaming-api.svc.us.c.replicate.net/v1/predictions/gcqxuulbl7fzat7667gsojyrhu", "get": "https://api.replicate.com/v1/predictions/gcqxuulbl7fzat7667gsojyrhu", "cancel": "https://api.replicate.com/v1/predictions/gcqxuulbl7fzat7667gsojyrhu/cancel" }, "version": "c0386a8ad96fea983e507fd410f9f93450c063f6e98cdc3fdd64684b8e343032" }Generated infrom_string grammar: root ::= [v] [e] [c] [2] [ ] [e] [f] [f] [e] [c] [t] [(] [v] [e] [c] [2] [ ] [p] [,] [ ] [f] [l] [o] [a] [t] [ ] [i] [,] [ ] [f] [l] [o] [a] [t] [ ] [t] [i] [m] [e] [)] [ ] [{] [<U+000A>] [ ] [ ] return-statement [<U+000A>] [}] return-statement ::= [r] [e] [t] [u] [r] [n] [ ] vec2-expression [;] vec2-expression ::= single-vec2-expression | single-vec2-expression operation vec2-expression single-vec2-expression ::= [v] [e] [c] [2] [(] scalar-expression [,] [ ] scalar-expression [)] operation ::= [ ] [+] [ ] | [ ] [-] [ ] | [ ] [*] [ ] | [ ] [/] [] scalar-expression ::= single-scalar-expression | single-scalar-expression operation scalar-expression single-scalar-expression ::= float-literal | variable | math-func [(] math-arg [)] float-literal ::= float-literal_11 [.] float-literal_12 variable ::= [p] [.] [x] | [p] [.] [y] | [i] | [t] [i] [m] [e] math-func ::= [s] [i] [n] | [c] [o] [s] | [t] [a] [n] | [l] [e] [n] [g] [t] [h] | [s] [q] [r] [t] | [e] [x] [p] math-arg ::= [p] [.] [x] | [p] [.] [y] | scalar-expression float-literal_11 ::= [0-9] float-literal_11 | [0-9] float-literal_12 ::= [0-9] float-literal_12 | [0-9] Llama.generate: prefix-match hit llama_print_timings: load time = 289.74 ms llama_print_timings: sample time = 1264.81 ms / 91 runs ( 13.90 ms per token, 71.95 tokens per second) llama_print_timings: prompt eval time = 0.00 ms / 1 tokens ( 0.00 ms per token, inf tokens per second) llama_print_timings: eval time = 1267.31 ms / 91 runs ( 13.93 ms per token, 71.81 tokens per second) llama_print_timings: total time = 2749.96 msPrediction
andreasjansson/plasma:c0386a8ad96fea983e507fd410f9f93450c063f6e98cdc3fdd64684b8e343032IDyvc4bk3baa2dq2j6vvtrejiwryStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
{}Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "andreasjansson/plasma:c0386a8ad96fea983e507fd410f9f93450c063f6e98cdc3fdd64684b8e343032", { input: {} } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run("andreasjansson/plasma:c0386a8ad96fea983e507fd410f9f93450c063f6e98cdc3fdd64684b8e343032") # The andreasjansson/plasma model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/andreasjansson/plasma/api#output-schema print(item, end="")To learn more, take a look at the guide on getting started with Python.
Run andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "c0386a8ad96fea983e507fd410f9f93450c063f6e98cdc3fdd64684b8e343032", "input": {} }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
vec2 effect(vec2 p, float i, float time) { return vec2(cos(i * sin(p.x * p.y) + time), sin(length(p.y - p.x) * i + time)); }{ "completed_at": "2023-12-05T14:25:44.391644Z", "created_at": "2023-12-05T14:25:42.541441Z", "data_removed": false, "error": null, "id": "yvc4bk3baa2dq2j6vvtrejiwry", "input": {}, "logs": "from_string grammar:\nroot ::= [v] [e] [c] [2] [ ] [e] [f] [f] [e] [c] [t] [(] [v] [e] [c] [2] [ ] [p] [,] [ ] [f] [l] [o] [a] [t] [ ] [i] [,] [ ] [f] [l] [o] [a] [t] [ ] [t] [i] [m] [e] [)] [ ] [{] [<U+000A>] [ ] [ ] return-statement [<U+000A>] [}]\nreturn-statement ::= [r] [e] [t] [u] [r] [n] [ ] vec2-expression [;] \nvec2-expression ::= single-vec2-expression | single-vec2-expression operation vec2-expression\nsingle-vec2-expression ::= [v] [e] [c] [2] [(] scalar-expression [,] [ ] scalar-expression [)] \noperation ::= [ ] [+] [ ] | [ ] [-] [ ] | [ ] [*] [ ] | [ ] [/] []\nscalar-expression ::= single-scalar-expression | single-scalar-expression operation scalar-expression\nsingle-scalar-expression ::= float-literal | variable | math-func [(] math-arg [)]\nfloat-literal ::= float-literal_11 [.] float-literal_12\nvariable ::= [p] [.] [x] | [p] [.] [y] | [i] | [t] [i] [m] [e] \nmath-func ::= [s] [i] [n] | [c] [o] [s] | [t] [a] [n] | [l] [e] [n] [g] [t] [h] | [s] [q] [r] [t] | [e] [x] [p] \nmath-arg ::= [p] [.] [x] | [p] [.] [y] | scalar-expression \nfloat-literal_11 ::= [0-9] float-literal_11 | [0-9]\nfloat-literal_12 ::= [0-9] float-literal_12 | [0-9]\nLlama.generate: prefix-match hit\nllama_print_timings: load time = 289.74 ms\nllama_print_timings: sample time = 883.17 ms / 58 runs ( 15.23 ms per token, 65.67 tokens per second)\nllama_print_timings: prompt eval time = 0.00 ms / 1 tokens ( 0.00 ms per token, inf tokens per second)\nllama_print_timings: eval time = 804.81 ms / 58 runs ( 13.88 ms per token, 72.07 tokens per second)\nllama_print_timings: total time = 1827.26 ms", "metrics": { "predict_time": 1.844234, "total_time": 1.850203 }, "output": [ "vec", "2", " effect", "(", "vec", "2", " p", ",", " float", " i", ",", " float", " time", ")", " {", "\n", " ", " return", " vec", "2", "(", "cos", "(", "i", " *", " sin", "(", "p", ".", "x", " *", " p", ".", "y", ")", " +", " time", "),", " sin", "(", "length", "(", "p", ".", "y", " -", " p", ".", "x", ")", " *", " i", " +", " time", "));", "\n", "}" ], "started_at": "2023-12-05T14:25:42.547410Z", "status": "succeeded", "urls": { "stream": "https://streaming-api.svc.us.c.replicate.net/v1/predictions/yvc4bk3baa2dq2j6vvtrejiwry", "get": "https://api.replicate.com/v1/predictions/yvc4bk3baa2dq2j6vvtrejiwry", "cancel": "https://api.replicate.com/v1/predictions/yvc4bk3baa2dq2j6vvtrejiwry/cancel" }, "version": "c0386a8ad96fea983e507fd410f9f93450c063f6e98cdc3fdd64684b8e343032" }Generated infrom_string grammar: root ::= [v] [e] [c] [2] [ ] [e] [f] [f] [e] [c] [t] [(] [v] [e] [c] [2] [ ] [p] [,] [ ] [f] [l] [o] [a] [t] [ ] [i] [,] [ ] [f] [l] [o] [a] [t] [ ] [t] [i] [m] [e] [)] [ ] [{] [<U+000A>] [ ] [ ] return-statement [<U+000A>] [}] return-statement ::= [r] [e] [t] [u] [r] [n] [ ] vec2-expression [;] vec2-expression ::= single-vec2-expression | single-vec2-expression operation vec2-expression single-vec2-expression ::= [v] [e] [c] [2] [(] scalar-expression [,] [ ] scalar-expression [)] operation ::= [ ] [+] [ ] | [ ] [-] [ ] | [ ] [*] [ ] | [ ] [/] [] scalar-expression ::= single-scalar-expression | single-scalar-expression operation scalar-expression single-scalar-expression ::= float-literal | variable | math-func [(] math-arg [)] float-literal ::= float-literal_11 [.] float-literal_12 variable ::= [p] [.] [x] | [p] [.] [y] | [i] | [t] [i] [m] [e] math-func ::= [s] [i] [n] | [c] [o] [s] | [t] [a] [n] | [l] [e] [n] [g] [t] [h] | [s] [q] [r] [t] | [e] [x] [p] math-arg ::= [p] [.] [x] | [p] [.] [y] | scalar-expression float-literal_11 ::= [0-9] float-literal_11 | [0-9] float-literal_12 ::= [0-9] float-literal_12 | [0-9] Llama.generate: prefix-match hit llama_print_timings: load time = 289.74 ms llama_print_timings: sample time = 883.17 ms / 58 runs ( 15.23 ms per token, 65.67 tokens per second) llama_print_timings: prompt eval time = 0.00 ms / 1 tokens ( 0.00 ms per token, inf tokens per second) llama_print_timings: eval time = 804.81 ms / 58 runs ( 13.88 ms per token, 72.07 tokens per second) llama_print_timings: total time = 1827.26 msPrediction
andreasjansson/plasma:c0386a8ad96fea983e507fd410f9f93450c063f6e98cdc3fdd64684b8e343032IDgkveoctbupgdxodmouwqmp2itqStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
{}Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "andreasjansson/plasma:c0386a8ad96fea983e507fd410f9f93450c063f6e98cdc3fdd64684b8e343032", { input: {} } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run("andreasjansson/plasma:c0386a8ad96fea983e507fd410f9f93450c063f6e98cdc3fdd64684b8e343032") # The andreasjansson/plasma model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/andreasjansson/plasma/api#output-schema print(item, end="")To learn more, take a look at the guide on getting started with Python.
Run andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "c0386a8ad96fea983e507fd410f9f93450c063f6e98cdc3fdd64684b8e343032", "input": {} }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
vec2 effect(vec2 p, float i, float time) { return vec2(cos(p.x * i + time), sin(p.y * i + time)) * vec2(sin(length(p.x - p.y) * i + time), cos(length(p.x - p.y) * i + time)) / vec2(i, i); }{ "completed_at": "2023-12-05T14:24:50.597369Z", "created_at": "2023-12-05T14:24:47.768540Z", "data_removed": false, "error": null, "id": "gkveoctbupgdxodmouwqmp2itq", "input": {}, "logs": "from_string grammar:\nroot ::= [v] [e] [c] [2] [ ] [e] [f] [f] [e] [c] [t] [(] [v] [e] [c] [2] [ ] [p] [,] [ ] [f] [l] [o] [a] [t] [ ] [i] [,] [ ] [f] [l] [o] [a] [t] [ ] [t] [i] [m] [e] [)] [ ] [{] [<U+000A>] [ ] [ ] return-statement [<U+000A>] [}] \nreturn-statement ::= [r] [e] [t] [u] [r] [n] [ ] vec2-expression [;]\nvec2-expression ::= single-vec2-expression | single-vec2-expression operation vec2-expression\nsingle-vec2-expression ::= [v] [e] [c] [2] [(] scalar-expression [,] [ ] scalar-expression [)] \noperation ::= [ ] [+] [ ] | [ ] [-] [ ] | [ ] [*] [ ] | [ ] [/] [ ] \nscalar-expression ::= single-scalar-expression | single-scalar-expression operation scalar-expression\nsingle-scalar-expression ::= float-literal | variable | math-func [(] math-arg [)] \nfloat-literal ::= float-literal_11 [.] float-literal_12\nvariable ::= [p] [.] [x] | [p] [.] [y] | [i] | [t] [i] [m] [e] \nmath-func ::= [s] [i] [n] | [c] [o] [s] | [t] [a] [n] | [l] [e] [n] [g] [t] [h] | [s] [q] [r] [t] | [e] [x] [p] \nmath-arg ::= [p] [.] [x] | [p] [.] [y] | scalar-expression\nfloat-literal_11 ::= [0-9] float-literal_11 | [0-9]\nfloat-literal_12 ::= [0-9] float-literal_12 | [0-9]\nLlama.generate: prefix-match hit\nllama_print_timings: load time = 289.74 ms\nllama_print_timings: sample time = 1293.41 ms / 92 runs ( 14.06 ms per token, 71.13 tokens per second)\nllama_print_timings: prompt eval time = 0.00 ms / 1 tokens ( 0.00 ms per token, inf tokens per second)\nllama_print_timings: eval time = 1278.00 ms / 92 runs ( 13.89 ms per token, 71.99 tokens per second)\nllama_print_timings: total time = 2794.10 ms", "metrics": { "predict_time": 2.806574, "total_time": 2.828829 }, "output": [ "v", "ec", "2", " effect", "(", "vec", "2", " p", ",", " float", " i", ",", " float", " time", ")", " {", "\n", " ", " return", " vec", "2", "(", "cos", "(", "p", ".", "x", " *", " i", " +", " time", "),", " sin", "(", "p", ".", "y", " *", " i", " +", " time", "))", " *", " vec", "2", "(", "sin", "(", "length", "(", "p", ".", "x", " -", " p", ".", "y", ")", " *", " i", " +", " time", "),", " cos", "(", "length", "(", "p", ".", "x", " -", " p", ".", "y", ")", " *", " i", " +", " time", "))", " /", " ", "vec", "2", "(", "i", ",", " i", ");", "\n", "}" ], "started_at": "2023-12-05T14:24:47.790795Z", "status": "succeeded", "urls": { "stream": "https://streaming-api.svc.us.c.replicate.net/v1/predictions/gkveoctbupgdxodmouwqmp2itq", "get": "https://api.replicate.com/v1/predictions/gkveoctbupgdxodmouwqmp2itq", "cancel": "https://api.replicate.com/v1/predictions/gkveoctbupgdxodmouwqmp2itq/cancel" }, "version": "c0386a8ad96fea983e507fd410f9f93450c063f6e98cdc3fdd64684b8e343032" }Generated infrom_string grammar: root ::= [v] [e] [c] [2] [ ] [e] [f] [f] [e] [c] [t] [(] [v] [e] [c] [2] [ ] [p] [,] [ ] [f] [l] [o] [a] [t] [ ] [i] [,] [ ] [f] [l] [o] [a] [t] [ ] [t] [i] [m] [e] [)] [ ] [{] [<U+000A>] [ ] [ ] return-statement [<U+000A>] [}] return-statement ::= [r] [e] [t] [u] [r] [n] [ ] vec2-expression [;] vec2-expression ::= single-vec2-expression | single-vec2-expression operation vec2-expression single-vec2-expression ::= [v] [e] [c] [2] [(] scalar-expression [,] [ ] scalar-expression [)] operation ::= [ ] [+] [ ] | [ ] [-] [ ] | [ ] [*] [ ] | [ ] [/] [ ] scalar-expression ::= single-scalar-expression | single-scalar-expression operation scalar-expression single-scalar-expression ::= float-literal | variable | math-func [(] math-arg [)] float-literal ::= float-literal_11 [.] float-literal_12 variable ::= [p] [.] [x] | [p] [.] [y] | [i] | [t] [i] [m] [e] math-func ::= [s] [i] [n] | [c] [o] [s] | [t] [a] [n] | [l] [e] [n] [g] [t] [h] | [s] [q] [r] [t] | [e] [x] [p] math-arg ::= [p] [.] [x] | [p] [.] [y] | scalar-expression float-literal_11 ::= [0-9] float-literal_11 | [0-9] float-literal_12 ::= [0-9] float-literal_12 | [0-9] Llama.generate: prefix-match hit llama_print_timings: load time = 289.74 ms llama_print_timings: sample time = 1293.41 ms / 92 runs ( 14.06 ms per token, 71.13 tokens per second) llama_print_timings: prompt eval time = 0.00 ms / 1 tokens ( 0.00 ms per token, inf tokens per second) llama_print_timings: eval time = 1278.00 ms / 92 runs ( 13.89 ms per token, 71.99 tokens per second) llama_print_timings: total time = 2794.10 msPrediction
andreasjansson/plasma:e636a18b4eb62730cf7a9706b65a5650b1917a15a0ee80499b45f27a673ad633ID4nngretbpx7f27bilqkujrquwqStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
{}Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "andreasjansson/plasma:e636a18b4eb62730cf7a9706b65a5650b1917a15a0ee80499b45f27a673ad633", { input: {} } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run("andreasjansson/plasma:e636a18b4eb62730cf7a9706b65a5650b1917a15a0ee80499b45f27a673ad633") # The andreasjansson/plasma model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/andreasjansson/plasma/api#output-schema print(item, end="")To learn more, take a look at the guide on getting started with Python.
Run andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "e636a18b4eb62730cf7a9706b65a5650b1917a15a0ee80499b45f27a673ad633", "input": {} }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
vec2 effect(vec2 p, float i, float time) { return vec2(cos(i * sin(time) * length(p.x)), sin(i * cos(time) * length(p.y))) / vec2(sin(length(p.x + time)), cos(length(p.y + time))) / vec2(i, i); }{ "completed_at": "2023-12-05T17:10:50.124570Z", "created_at": "2023-12-05T17:10:45.653607Z", "data_removed": false, "error": null, "id": "4nngretbpx7f27bilqkujrquwq", "input": {}, "logs": "from_string grammar:\nroot ::= [v] [e] [c] [2] [ ] [e] [f] [f] [e] [c] [t] [(] [v] [e] [c] [2] [ ] [p] [,] [ ] [f] [l] [o] [a] [t] [ ] [i] [,] [ ] [f] [l] [o] [a] [t] [ ] [t] [i] [m] [e] [)] [ ] [{] [<U+000A>] [ ] [ ] return-statement [<U+000A>] [}]\nreturn-statement ::= [r] [e] [t] [u] [r] [n] [ ] vec2-expression [;]\nvec2-expression ::= single-vec2-expression | single-vec2-expression operation vec2-expression\nsingle-vec2-expression ::= [v] [e] [c] [2] [(] scalar-expression [,] [ ] scalar-expression [)]\noperation ::= [ ] [+] [ ] | [ ] [-] [ ] | [ ] [*] [ ] | [ ] [/] [ ]\nscalar-expression ::= single-scalar-expression | single-scalar-expression operation scalar-expression\nsingle-scalar-expression ::= float-literal | variable | math-func [(] math-arg [)]\nfloat-literal ::= float-literal_11 [.] float-literal_12\nvariable ::= [p] [.] [x] | [p] [.] [y] | [i] | [t] [i] [m] [e]\nmath-func ::= [s] [i] [n] | [c] [o] [s] | [t] [a] [n] | [l] [e] [n] [g] [t] [h] | [s] [q] [r] [t] | [e] [x] [p]\nmath-arg ::= [p] [.] [x] | [p] [.] [y] | scalar-expression\nfloat-literal_11 ::= [0-9] float-literal_11 | [0-9]\nfloat-literal_12 ::= [0-9] float-literal_12 | [0-9]\nLlama.generate: prefix-match hit\nllama_print_timings: load time = 286.50 ms\nllama_print_timings: sample time = 2979.38 ms / 88 runs ( 33.86 ms per token, 29.54 tokens per second)\nllama_print_timings: prompt eval time = 0.00 ms / 1 tokens ( 0.00 ms per token, inf tokens per second)\nllama_print_timings: eval time = 1255.64 ms / 88 runs ( 14.27 ms per token, 70.08 tokens per second)\nllama_print_timings: total time = 4448.17 ms", "metrics": { "predict_time": 4.4615, "total_time": 4.470963 }, "output": [ "vec", "2", " effect", "(", "vec", "2", " p", ",", " float", " i", ",", " float", " time", ")", " {", "\n", " ", " return", " vec", "2", "(", "cos", "(", "i", " *", " sin", "(", "time", ")", " *", " length", "(", "p", ".", "x", ")),", " sin", "(", "i", " *", " cos", "(", "time", ")", " *", " length", "(", "p", ".", "y", ")))", " /", " ", "vec", "2", "(", "sin", "(", "length", "(", "p", ".", "x", " +", " time", ")),", " cos", "(", "length", "(", "p", ".", "y", " +", " time", ")))", " /", " ", "vec", "2", "(", "i", ",", " i", ");", "\n", "}" ], "started_at": "2023-12-05T17:10:45.663070Z", "status": "succeeded", "urls": { "stream": "https://streaming-api.svc.us.c.replicate.net/v1/predictions/4nngretbpx7f27bilqkujrquwq", "get": "https://api.replicate.com/v1/predictions/4nngretbpx7f27bilqkujrquwq", "cancel": "https://api.replicate.com/v1/predictions/4nngretbpx7f27bilqkujrquwq/cancel" }, "version": "e636a18b4eb62730cf7a9706b65a5650b1917a15a0ee80499b45f27a673ad633" }Generated infrom_string grammar: root ::= [v] [e] [c] [2] [ ] [e] [f] [f] [e] [c] [t] [(] [v] [e] [c] [2] [ ] [p] [,] [ ] [f] [l] [o] [a] [t] [ ] [i] [,] [ ] [f] [l] [o] [a] [t] [ ] [t] [i] [m] [e] [)] [ ] [{] [<U+000A>] [ ] [ ] return-statement [<U+000A>] [}] return-statement ::= [r] [e] [t] [u] [r] [n] [ ] vec2-expression [;] vec2-expression ::= single-vec2-expression | single-vec2-expression operation vec2-expression single-vec2-expression ::= [v] [e] [c] [2] [(] scalar-expression [,] [ ] scalar-expression [)] operation ::= [ ] [+] [ ] | [ ] [-] [ ] | [ ] [*] [ ] | [ ] [/] [ ] scalar-expression ::= single-scalar-expression | single-scalar-expression operation scalar-expression single-scalar-expression ::= float-literal | variable | math-func [(] math-arg [)] float-literal ::= float-literal_11 [.] float-literal_12 variable ::= [p] [.] [x] | [p] [.] [y] | [i] | [t] [i] [m] [e] math-func ::= [s] [i] [n] | [c] [o] [s] | [t] [a] [n] | [l] [e] [n] [g] [t] [h] | [s] [q] [r] [t] | [e] [x] [p] math-arg ::= [p] [.] [x] | [p] [.] [y] | scalar-expression float-literal_11 ::= [0-9] float-literal_11 | [0-9] float-literal_12 ::= [0-9] float-literal_12 | [0-9] Llama.generate: prefix-match hit llama_print_timings: load time = 286.50 ms llama_print_timings: sample time = 2979.38 ms / 88 runs ( 33.86 ms per token, 29.54 tokens per second) llama_print_timings: prompt eval time = 0.00 ms / 1 tokens ( 0.00 ms per token, inf tokens per second) llama_print_timings: eval time = 1255.64 ms / 88 runs ( 14.27 ms per token, 70.08 tokens per second) llama_print_timings: total time = 4448.17 msPrediction
andreasjansson/plasma:cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952ID9xkk5e6x8srgg0ckam2b4b49fwStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
{}Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "andreasjansson/plasma:cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952", { input: {} } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run("andreasjansson/plasma:cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952") # The andreasjansson/plasma model can stream output as it's running. # The predict method returns an iterator, and you can iterate over that output. for item in output: # https://replicate.com/andreasjansson/plasma/api#output-schema print(item, end="")To learn more, take a look at the guide on getting started with Python.
Run andreasjansson/plasma using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952", "input": {} }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
vec2 effect(vec2 p, float i, float time) { return vec2(sin(p.x * 15.0 + sin(p.y * 15.0) + time), cos(p.y * 30.0 - cos(p.x * 20.0) + time)) / vec2(i, i); }{ "completed_at": "2024-11-22T17:56:45.450258Z", "created_at": "2024-11-22T17:56:42.438000Z", "data_removed": false, "error": null, "id": "9xkk5e6x8srgg0ckam2b4b49fw", "input": {}, "logs": "from_string grammar:\nroot ::= [v] [e] [c] [2] [ ] [e] [f] [f] [e] [c] [t] [(] [v] [e] [c] [2] [ ] [p] [,] [ ] [f] [l] [o] [a] [t] [ ] [i] [,] [ ] [f] [l] [o] [a] [t] [ ] [t] [i] [m] [e] [)] [ ] [{] [<U+000A>] [ ] [ ] return-statement [<U+000A>] [}]\nreturn-statement ::= [r] [e] [t] [u] [r] [n] [ ] vec2-expression [;] \nvec2-expression ::= single-vec2-expression | single-vec2-expression operation vec2-expression \nsingle-vec2-expression ::= [v] [e] [c] [2] [(] scalar-expression [,] [ ] scalar-expression [)]\noperation ::= [ ] [+] [ ] | [ ] [-] [ ] | [ ] [*] [ ] | [ ] [/] [ ] \nscalar-expression ::= single-scalar-expression | single-scalar-expression operation scalar-expression\nsingle-scalar-expression ::= float-literal | variable | math-func [(] math-arg [)]\nfloat-literal ::= float-literal_11 [.] float-literal_12 \nvariable ::= [p] [.] [x] | [p] [.] [y] | [i] | [t] [i] [m] [e] \nmath-func ::= [s] [i] [n] | [c] [o] [s] | [t] [a] [n] | [l] [e] [n] [g] [t] [h] | [s] [q] [r] [t] | [e] [x] [p] \nmath-arg ::= [p] [.] [x] | [p] [.] [y] | scalar-expression\nfloat-literal_11 ::= [0-9] float-literal_11 | [0-9] \nfloat-literal_12 ::= [0-9] float-literal_12 | [0-9] \nLlama.generate: prefix-match hit\nllama_print_timings: load time = 8320.92 ms\nllama_print_timings: sample time = 1518.21 ms / 87 runs ( 17.45 ms per token, 57.30 tokens per second)\nllama_print_timings: prompt eval time = 0.00 ms / 1 tokens ( 0.00 ms per token, inf tokens per second)\nllama_print_timings: eval time = 1263.33 ms / 87 runs ( 14.52 ms per token, 68.87 tokens per second)\nllama_print_timings: total time = 2994.77 ms", "metrics": { "predict_time": 3.004472856, "total_time": 3.012258 }, "output": [ "vec", "2", " effect", "(", "vec", "2", " p", ",", " float", " i", ",", " float", " time", ")", " {", "\n", " ", " return", " vec", "2", "(", "sin", "(", "p", ".", "x", " *", " ", "1", "5", ".", "0", " +", " sin", "(", "p", ".", "y", " *", " ", "1", "5", ".", "0", ")", " +", " time", "),", " cos", "(", "p", ".", "y", " *", " ", "3", "0", ".", "0", " -", " cos", "(", "p", ".", "x", " *", " ", "2", "0", ".", "0", ")", " +", " time", "))", " /", " ", "vec", "2", "(", "i", ",", " i", ");", "\n", "}" ], "started_at": "2024-11-22T17:56:42.445785Z", "status": "succeeded", "urls": { "stream": "https://stream-g.svc.us.c.replicate.net/v1/streams/lqcqzgl62at2kcdhtlfpgfbblifcfqoyoxnewmdzq2ccyy24egka", "get": "https://api.replicate.com/v1/predictions/9xkk5e6x8srgg0ckam2b4b49fw", "cancel": "https://api.replicate.com/v1/predictions/9xkk5e6x8srgg0ckam2b4b49fw/cancel" }, "version": "cc8fda9d792ea48be0bd70b66966614acdee2e2b7612fbb820ed1908b410a952" }Generated infrom_string grammar: root ::= [v] [e] [c] [2] [ ] [e] [f] [f] [e] [c] [t] [(] [v] [e] [c] [2] [ ] [p] [,] [ ] [f] [l] [o] [a] [t] [ ] [i] [,] [ ] [f] [l] [o] [a] [t] [ ] [t] [i] [m] [e] [)] [ ] [{] [<U+000A>] [ ] [ ] return-statement [<U+000A>] [}] return-statement ::= [r] [e] [t] [u] [r] [n] [ ] vec2-expression [;] vec2-expression ::= single-vec2-expression | single-vec2-expression operation vec2-expression single-vec2-expression ::= [v] [e] [c] [2] [(] scalar-expression [,] [ ] scalar-expression [)] operation ::= [ ] [+] [ ] | [ ] [-] [ ] | [ ] [*] [ ] | [ ] [/] [ ] scalar-expression ::= single-scalar-expression | single-scalar-expression operation scalar-expression single-scalar-expression ::= float-literal | variable | math-func [(] math-arg [)] float-literal ::= float-literal_11 [.] float-literal_12 variable ::= [p] [.] [x] | [p] [.] [y] | [i] | [t] [i] [m] [e] math-func ::= [s] [i] [n] | [c] [o] [s] | [t] [a] [n] | [l] [e] [n] [g] [t] [h] | [s] [q] [r] [t] | [e] [x] [p] math-arg ::= [p] [.] [x] | [p] [.] [y] | scalar-expression float-literal_11 ::= [0-9] float-literal_11 | [0-9] float-literal_12 ::= [0-9] float-literal_12 | [0-9] Llama.generate: prefix-match hit llama_print_timings: load time = 8320.92 ms llama_print_timings: sample time = 1518.21 ms / 87 runs ( 17.45 ms per token, 57.30 tokens per second) llama_print_timings: prompt eval time = 0.00 ms / 1 tokens ( 0.00 ms per token, inf tokens per second) llama_print_timings: eval time = 1263.33 ms / 87 runs ( 14.52 ms per token, 68.87 tokens per second) llama_print_timings: total time = 2994.77 ms
Want to make some of these yourself?
Run this model