Instructions to use InfiniAILab/CodeDrafter-500M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use InfiniAILab/CodeDrafter-500M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="InfiniAILab/CodeDrafter-500M")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("InfiniAILab/CodeDrafter-500M") model = AutoModelForCausalLM.from_pretrained("InfiniAILab/CodeDrafter-500M") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use InfiniAILab/CodeDrafter-500M with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "InfiniAILab/CodeDrafter-500M" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "InfiniAILab/CodeDrafter-500M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/InfiniAILab/CodeDrafter-500M
- SGLang
How to use InfiniAILab/CodeDrafter-500M with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "InfiniAILab/CodeDrafter-500M" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "InfiniAILab/CodeDrafter-500M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "InfiniAILab/CodeDrafter-500M" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "InfiniAILab/CodeDrafter-500M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use InfiniAILab/CodeDrafter-500M with Docker Model Runner:
docker model run hf.co/InfiniAILab/CodeDrafter-500M
Zhuoming Chen commited on
Update README.md
Browse files
README.md
CHANGED
|
@@ -17,4 +17,16 @@ tags:
|
|
| 17 |
A draft model for Llama3.1/3.2/3.3 series models, specialized in python coding. This model is finetuned from the first 4 layers of facebook/layerskip-llama3.2-1B.
|
| 18 |
|
| 19 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 20 |
|
|
|
|
| 17 |
A draft model for Llama3.1/3.2/3.3 series models, specialized in python coding. This model is finetuned from the first 4 layers of facebook/layerskip-llama3.2-1B.
|
| 18 |
|
| 19 |
|
| 20 |
+
## Citation
|
| 21 |
+
|
| 22 |
+
```bibtex
|
| 23 |
+
@article{chen2024sequoia,
|
| 24 |
+
title={Sequoia: Scalable, Robust, and Hardware-aware Speculative Decoding},
|
| 25 |
+
author={Chen, Zhuoming and May, Avner and Svirschevski, Ruslan and Huang, Yuhsun and Ryabinin, Max and Jia, Zhihao and Chen, Beidi},
|
| 26 |
+
journal={arXiv preprint arXiv:2402.12374},
|
| 27 |
+
year={2024}
|
| 28 |
+
}
|
| 29 |
+
```
|
| 30 |
+
|
| 31 |
+
|
| 32 |
|