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(5 versions)

MAX Model

BF16

GPU

This version is not quantized and a GPU is recommended.

Install our magic package manager:
```
curl -ssL https://magic.modular.com/ | bash
```
Then run the source command that's printed in your terminal.

Install Max Pipelines in order to run this model.

magic global install max-pipelines && magic global update

Start a local endpoint for Qwen2.5-Instruct/0.5B:

max-pipelines serve --huggingface-repo-id=Qwen/Qwen2.5-0.5B-Instruct

The endpoint is ready when you see the URI printed in your terminal:

Server ready on http://0.0.0.0:8000 (Press CTRL+C to quit)

Now open another terminal to send a request using curl:

curl -N http://0.0.0.0:8000/v1/chat/completions -H "Content-Type: application/json" -d '{
    "model": "Qwen/Qwen2.5-0.5B-Instruct",
    "stream": true,
    "messages": [
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Who won the World Series in 2020?"}
    ]
}' | grep -o '"content":"[^"]*"' | sed 's/"content":"//g' | sed 's/"//g' | tr -d '
' | sed 's/\n//g'

🎉 Hooray! You’re running Generative AI. Our goal is to make this as easy as possible.

Deploy this model to cloud

Qwen2.5-Instruct

Qwen2.5 represents the cutting-edge in large language models, with models ranging from 0.5 to 72 billion parameters. Key advancements over its predecessor, Qwen2, include:

Enhanced knowledge base, significantly improving skills in coding and mathematics.
Better performance in instruction following, long text generation over 8,000 tokens, and understanding and generating structured data like JSON.
Enhanced resilience to diverse system prompts, making it suitable for chatbots and role-playing applications.
Long-context Support capable of handling up to 128,000 tokens.
Multilingual capabilities in more than 29 languages including Chinese, English, French, Spanish, and Japanese.

This repository contains the base 0.5B Qwen2.5 model featuring:

Type: Causal Language Model
Training Stage: Pretraining
Architecture: Transformer with RoPE, SwiGLU, RMSNorm, Attention QKV bias, and tied word embeddings
Number of Parameters: 0.49B
Number of Parameters (Non-Embedding): 0.36B
Number of Layers: 24
Attention Heads (GQA): 14 for Q, 2 for KV
Context Length: Up to 32,768 tokens

Recommendation: Base models are not suited for conversational tasks. Post-training techniques like SFT or RLHF are advised.

For further insights, visit our blog, GitHub, and Documentation.

Evaluation & Performance

Comprehensive evaluation results can be explored in our blog. GPU memory requirements and throughput data are available here.

Citation

If you find our work beneficial, please cite us:

@misc{qwen2.5,
    title = {Qwen2.5: A Party of Foundation Models},
    url = {https://qwenlm.github.io/blog/qwen2.5/},
    author = {Qwen Team},
    month = {September},
    year = {2024}
}

@article{qwen2,
title={Qwen2 Technical Report},
author={An Yang et al.},
journal={arXiv preprint arXiv:2407.10671},
year={2024}
}

Metadata

architectures.0	Qwen2ForCausalLM
model_type	qwen2

Version: 0.5B GPU BF16

This code works on compatible Linux machines.
We are actively working on enabling MAX Serve for MacOS ARM64 as well.

You can quickly deploy Qwen2.5-Instruct-0.5B to an endpoint using our MAX container. It includes the latest version of MAX with GPU support and our Python-based inference server called MAX Serve.

With the following Docker command, you’ll get an OpenAI-compatible endpoint running Qwen2.5-Instruct-0.5B:

docker run --gpus 1 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_HUB_ENABLE_HF_TRANSFER=1" \
    --env "HF_TOKEN=" \
    -p 8000:8000 \
    docker.modular.com/modular/max-openai-api:nightly \
    --huggingface-repo-id Qwen/Qwen2.5-0.5B-Instruct

In order to download the model from Hugging Face, you just need to fill in the HF_TOKEN value with your access token, unless the model is from https://huggingface.co/modularai.

Learn more

For more information about the container image, see the MAX container documentation.

To learn more about how to deploy MAX to the cloud, check out our MAX Serve tutorials.

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ChatMODEL CLASS

MAX Model

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Qwen/Qwen2.5-0.5B-Instruct

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