zsxkib / qwen2-7b-instruct

Qwen 2: A 7 billion parameter language model from Alibaba Cloud, fine tuned for chat completions

Cold

Public
1.7K runs
L40S
GitHub
Paper
License

Run with an API

Playground API Examples README Versions

Prediction

zsxkib/qwen2-7b-instruct:5324178307f5ec0239326b429d6b64ae338cd6b51fbe234402a55537a9998ac4

Model

zsxkib/qwen2-7b-instruct:53241783

x29zpf3pyhrgm0cga1hsgaqfhr

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

1m 36s

Created

11 months ago

Input

top_k: 1
top_p: 1
prompt: Tell me a joke about only having 7 billion parameters
model_type: Qwen2-7B-Instruct
temperature: 1
system_prompt: You are a funny and helpful assistant.
max_new_tokens: 512
repetition_penalty: 1

{
  "top_k": 1,
  "top_p": 1,
  "prompt": "Tell me a joke about only having 7 billion parameters",
  "model_type": "Qwen2-7B-Instruct",
  "temperature": 1,
  "system_prompt": "You are a funny and 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 zsxkib/qwen2-7b-instruct using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "zsxkib/qwen2-7b-instruct:5324178307f5ec0239326b429d6b64ae338cd6b51fbe234402a55537a9998ac4",
  {
    input: {
      top_k: 1,
      top_p: 1,
      prompt: "Tell me a joke about only having 7 billion parameters",
      model_type: "Qwen2-7B-Instruct",
      temperature: 1,
      system_prompt: "You are a funny and 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 zsxkib/qwen2-7b-instruct using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "zsxkib/qwen2-7b-instruct:5324178307f5ec0239326b429d6b64ae338cd6b51fbe234402a55537a9998ac4",
    input={
        "top_k": 1,
        "top_p": 1,
        "prompt": "Tell me a joke about only having 7 billion parameters",
        "model_type": "Qwen2-7B-Instruct",
        "temperature": 1,
        "system_prompt": "You are a funny and helpful assistant.",
        "max_new_tokens": 512,
        "repetition_penalty": 1
    }
)

# The zsxkib/qwen2-7b-instruct 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/zsxkib/qwen2-7b-instruct/api#output-schema
    print(item, end="")

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

Run zsxkib/qwen2-7b-instruct 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": "zsxkib/qwen2-7b-instruct:5324178307f5ec0239326b429d6b64ae338cd6b51fbe234402a55537a9998ac4",
    "input": {
      "top_k": 1,
      "top_p": 1,
      "prompt": "Tell me a joke about only having 7 billion parameters",
      "model_type": "Qwen2-7B-Instruct",
      "temperature": 1,
      "system_prompt": "You are a funny and 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.