typetext
{
"debug": false,
"max_new_tokens": 500,
"min_new_tokens": -1,
"prompt": "[INST]\nGiven the following JSON weather data, write a weather report: \n\n{\n \"location\": \"San Francisco, CA\",\n \"temperature: \"65ºF\",\n \"forecast_high\": \"81ºF\",\n \"forecast_low\": \"63ºF\"\n \"time\": \"2023-10-09 10:00\"\n}\n\nYou must only report on the data that is provided in the JSON. Do not mention any weather details that are outside the scope of the provided JSON.. Do not mention the JSON context data.\n\nAll responses must sound like a human meteorologist.\n\n[/INST]",
"temperature": 0.7,
"top_k": 50,
"top_p": 0.9
}npm install replicate
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=r8_Idj**********************************
This is your API token. Keep it to yourself.
import Replicate from "replicate";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});
Run mistralai/mistral-7b-instruct-v0.1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"mistralai/mistral-7b-instruct-v0.1:83b6a56e7c828e667f21fd596c338fd4f0039b46bcfa18d973e8e70e455fda70",
{
input: {
debug: false,
max_new_tokens: 500,
min_new_tokens: -1,
prompt: "[INST]\nGiven the following JSON weather data, write a weather report: \n\n{\n \"location\": \"San Francisco, CA\",\n \"temperature: \"65ºF\",\n \"forecast_high\": \"81ºF\",\n \"forecast_low\": \"63ºF\"\n \"time\": \"2023-10-09 10:00\"\n}\n\nYou must only report on the data that is provided in the JSON. Do not mention any weather details that are outside the scope of the provided JSON.. Do not mention the JSON context data.\n\nAll responses must sound like a human meteorologist.\n\n[/INST]",
temperature: 0.7,
top_k: 50,
top_p: 0.9
}
}
);
console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=r8_Idj**********************************
This is your API token. Keep it to yourself.
import replicate
Run mistralai/mistral-7b-instruct-v0.1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"mistralai/mistral-7b-instruct-v0.1:83b6a56e7c828e667f21fd596c338fd4f0039b46bcfa18d973e8e70e455fda70",
input={
"debug": False,
"max_new_tokens": 500,
"min_new_tokens": -1,
"prompt": "[INST]\nGiven the following JSON weather data, write a weather report: \n\n{\n \"location\": \"San Francisco, CA\",\n \"temperature: \"65ºF\",\n \"forecast_high\": \"81ºF\",\n \"forecast_low\": \"63ºF\"\n \"time\": \"2023-10-09 10:00\"\n}\n\nYou must only report on the data that is provided in the JSON. Do not mention any weather details that are outside the scope of the provided JSON.. Do not mention the JSON context data.\n\nAll responses must sound like a human meteorologist.\n\n[/INST]",
"temperature": 0.7,
"top_k": 50,
"top_p": 0.9
}
)
# The mistralai/mistral-7b-instruct-v0.1 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/mistralai/mistral-7b-instruct-v0.1/api#output-schema
print(item, end="")
To learn more, take a look at the guide on getting started with Python.
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=r8_Idj**********************************
This is your API token. Keep it to yourself.
Run mistralai/mistral-7b-instruct-v0.1 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": "mistralai/mistral-7b-instruct-v0.1:83b6a56e7c828e667f21fd596c338fd4f0039b46bcfa18d973e8e70e455fda70",
"input": {
"debug": false,
"max_new_tokens": 500,
"min_new_tokens": -1,
"prompt": "[INST]\\nGiven the following JSON weather data, write a weather report: \\n\\n{\\n \\"location\\": \\"San Francisco, CA\\",\\n \\"temperature: \\"65ºF\\",\\n \\"forecast_high\\": \\"81ºF\\",\\n \\"forecast_low\\": \\"63ºF\\"\\n \\"time\\": \\"2023-10-09 10:00\\"\\n}\\n\\nYou must only report on the data that is provided in the JSON. Do not mention any weather details that are outside the scope of the provided JSON.. Do not mention the JSON context data.\\n\\nAll responses must sound like a human meteorologist.\\n\\n[/INST]",
"temperature": 0.7,
"top_k": 50,
"top_p": 0.9
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Good morning! Today in San Francisco, CA, the temperature is currently 65 degrees Fahrenheit. The forecast for the day calls for a high of 81 degrees and a low of 63 degrees. It's a beautiful day to explore the city and enjoy the outdoors. Make sure to stay hydrated and wear sunscreen if you plan on spending time in the sun. Have a great day!
{
"id": "quh3kf3b23ftbag2dvjtebysfy",
"model": "mistralai/mistral-7b-instruct-v0.1",
"version": "83b6a56e7c828e667f21fd596c338fd4f0039b46bcfa18d973e8e70e455fda70",
"input": {
"debug": false,
"max_new_tokens": 500,
"min_new_tokens": -1,
"prompt": "[INST]\nGiven the following JSON weather data, write a weather report: \n\n{\n \"location\": \"San Francisco, CA\",\n \"temperature: \"65ºF\",\n \"forecast_high\": \"81ºF\",\n \"forecast_low\": \"63ºF\"\n \"time\": \"2023-10-09 10:00\"\n}\n\nYou must only report on the data that is provided in the JSON. Do not mention any weather details that are outside the scope of the provided JSON.. Do not mention the JSON context data.\n\nAll responses must sound like a human meteorologist.\n\n[/INST]",
"temperature": 0.7,
"top_k": 50,
"top_p": 0.9
},
"logs": "Your formatted prompt is:\n[INST] [INST]\nGiven the following JSON weather data, write a weather report:\n{\n\"location\": \"San Francisco, CA\",\n\"temperature: \"65ºF\",\n\"forecast_high\": \"81ºF\",\n\"forecast_low\": \"63ºF\"\n\"time\": \"2023-10-09 10:00\"\n}\nYou must only report on the data that is provided in the JSON. Do not mention any weather details that are outside the scope of the provided JSON.. Do not mention the JSON context data.\nAll responses must sound like a human meteorologist. [/INST]\nDisabling loras\nNo loras were ever loaded, nothing to disable.\nNot using LoRA\nTokens: tensor([[ 1, 733, 16289, 28793, 733, 16289, 28793, 13, 28777, 5067,\n272, 2296, 9292, 8086, 1178, 28725, 3324, 264, 8086, 2264,\n28747, 28705, 13, 13, 28751, 13, 28705, 345, 2733, 1264,\n345, 17904, 9686, 28725, 9461, 548, 13, 28705, 345, 28707,\n16561, 28747, 345, 28784, 28782, 28936, 28765, 548, 13, 28705,\n345, 994, 2867, 28730, 9301, 1264, 345, 28783, 28740, 28936,\n28765, 548, 13, 28705, 345, 994, 2867, 28730, 9381, 1264,\n345, 28784, 28770, 28936, 28765, 28739, 13, 28705, 345, 1536,\n1264, 345, 28750, 28734, 28750, 28770, 28733, 28740, 28734, 28733,\n28734, 28774, 28705, 28740, 28734, 28747, 28734, 28734, 28739, 13,\n28752, 13, 13, 1976, 1580, 865, 2264, 356, 272, 1178,\n369, 349, 3857, 297, 272, 9292, 28723, 2378, 459, 4389,\n707, 8086, 4162, 369, 460, 3536, 272, 8593, 302, 272,\n3857, 9292, 568, 2378, 459, 4389, 272, 9292, 2758, 1178,\n28723, 13, 13, 2595, 14915, 1580, 2622, 737, 264, 2930,\n1424, 28706, 271, 12418, 28723, 733, 28748, 16289, 28793]],\ndevice='cuda:0')\nThe attention mask and the pad token id were not set. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.\nSetting `pad_token_id` to `eos_token_id`:2 for open-end generation.\nhostname: model-83b6a56e-94fe09a4acfa2b19-gpu-a40-555b6fdf4f-9kdqv",
"output": [
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"morning! ",
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],
"data_removed": false,
"error": null,
"source": "web",
"status": "succeeded",
"created_at": "2023-10-09T22:24:14.366475Z",
"started_at": "2023-10-09T22:24:14.404453Z",
"completed_at": "2023-10-09T22:24:20.548956Z",
"urls": {
"cancel": "https://api.replicate.com/v1/predictions/quh3kf3b23ftbag2dvjtebysfy/cancel",
"get": "https://api.replicate.com/v1/predictions/quh3kf3b23ftbag2dvjtebysfy"
},
"metrics": {
"predict_time": 6.144503,
"total_time": 6.182481
}
}