lucataco / qwen1.5-0.5b

{
  "top_k": 1,
  "top_p": 1,
  "prompt": "Give me a short introduction to large language model.",
  "temperature": 1,
  "system_prompt": "You are a helpful assistant.",
  "max_new_tokens": 512,
  "repetition_penalty": 1
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run lucataco/qwen1.5-0.5b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/qwen1.5-0.5b:aeb5ca9e257ceb13ce4c781f292ef4cb0e09a12528e8ef1a07f3d98439a6c9d5",
  {
    input: {
      top_k: 1,
      top_p: 1,
      prompt: "Give me a short introduction to large language model.",
      temperature: 1,
      system_prompt: "You are a helpful assistant.",
      max_new_tokens: 512,
      repetition_penalty: 1
    }
  }
);

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 replicate

Import the client:

import replicate

Run lucataco/qwen1.5-0.5b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/qwen1.5-0.5b:aeb5ca9e257ceb13ce4c781f292ef4cb0e09a12528e8ef1a07f3d98439a6c9d5",
    input={
        "top_k": 1,
        "top_p": 1,
        "prompt": "Give me a short introduction to large language model.",
        "temperature": 1,
        "system_prompt": "You are a helpful assistant.",
        "max_new_tokens": 512,
        "repetition_penalty": 1
    }
)

# The lucataco/qwen1.5-0.5b 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/lucataco/qwen1.5-0.5b/api#output-schema
    print(item, end="")

To learn more, take a look at the guide on getting started with Python.

Run lucataco/qwen1.5-0.5b 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": "lucataco/qwen1.5-0.5b:aeb5ca9e257ceb13ce4c781f292ef4cb0e09a12528e8ef1a07f3d98439a6c9d5",
    "input": {
      "top_k": 1,
      "top_p": 1,
      "prompt": "Give me a short introduction to large language model.",
      "temperature": 1,
      "system_prompt": "You are a helpful assistant.",
      "max_new_tokens": 512,
      "repetition_penalty": 1
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

A large language model is a type of artificial intelligence system that is designed to generate human-like text based on a large corpus of text data. These models are trained on a large dataset of text, which allows them to learn patterns and relationships in language that are not present in the training data. Once trained, large language models can be used to generate text in a variety of domains, such as natural language processing, machine translation, and text generation. They are often used in a variety of applications, such as chatbots, virtual assistants, and language translation services.

{
  "completed_at": "2024-02-06T23:16:36.825003Z",
  "created_at": "2024-02-06T23:16:22.407921Z",
  "data_removed": false,
  "error": null,
  "id": "yqrpa5zczjhwsnz243px3qyt7q",
  "input": {
    "top_k": 1,
    "top_p": 1,
    "prompt": "Give me a short introduction to large language model.",
    "temperature": 1,
    "system_prompt": "You are a helpful assistant.",
    "max_new_tokens": 512,
    "repetition_penalty": 1
  },
  "logs": "Using seed: 841683831\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`:151645 for open-end generation.",
  "metrics": {
    "predict_time": 14.406418,
    "total_time": 14.417082
  },
  "output": [
    "\n\n",
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  ],
  "started_at": "2024-02-06T23:16:22.418585Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/yqrpa5zczjhwsnz243px3qyt7q",
    "cancel": "https://api.replicate.com/v1/predictions/yqrpa5zczjhwsnz243px3qyt7q/cancel"
  },
  "version": "aeb5ca9e257ceb13ce4c781f292ef4cb0e09a12528e8ef1a07f3d98439a6c9d5"
}

Generated in

14.4 seconds

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