Instructions to use zhenchonghu/starcoder2-3b-alpaca-qlora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use zhenchonghu/starcoder2-3b-alpaca-qlora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("bigcode/starcoder2-3b") model = PeftModel.from_pretrained(base_model, "zhenchonghu/starcoder2-3b-alpaca-qlora") - Transformers
How to use zhenchonghu/starcoder2-3b-alpaca-qlora with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="zhenchonghu/starcoder2-3b-alpaca-qlora")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("zhenchonghu/starcoder2-3b-alpaca-qlora", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use zhenchonghu/starcoder2-3b-alpaca-qlora with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "zhenchonghu/starcoder2-3b-alpaca-qlora" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "zhenchonghu/starcoder2-3b-alpaca-qlora", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/zhenchonghu/starcoder2-3b-alpaca-qlora
- SGLang
How to use zhenchonghu/starcoder2-3b-alpaca-qlora 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 "zhenchonghu/starcoder2-3b-alpaca-qlora" \ --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": "zhenchonghu/starcoder2-3b-alpaca-qlora", "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 "zhenchonghu/starcoder2-3b-alpaca-qlora" \ --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": "zhenchonghu/starcoder2-3b-alpaca-qlora", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use zhenchonghu/starcoder2-3b-alpaca-qlora with Docker Model Runner:
docker model run hf.co/zhenchonghu/starcoder2-3b-alpaca-qlora
- Xet hash:
- 36a04aad254ae889a7fd1b5ecf03759cd470cafb83cd061609e1c21990a77520
- Size of remote file:
- 5.84 kB
- SHA256:
- f4515e1e1375aa95120f2938253afccb5b62b14e46c38b2725693ceb241b84ea
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