Instructions to use gammatau/starcoder-1b-fit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gammatau/starcoder-1b-fit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="gammatau/starcoder-1b-fit")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("gammatau/starcoder-1b-fit") model = AutoModelForCausalLM.from_pretrained("gammatau/starcoder-1b-fit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use gammatau/starcoder-1b-fit with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "gammatau/starcoder-1b-fit" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "gammatau/starcoder-1b-fit", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/gammatau/starcoder-1b-fit
- SGLang
How to use gammatau/starcoder-1b-fit 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 "gammatau/starcoder-1b-fit" \ --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": "gammatau/starcoder-1b-fit", "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 "gammatau/starcoder-1b-fit" \ --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": "gammatau/starcoder-1b-fit", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use gammatau/starcoder-1b-fit with Docker Model Runner:
docker model run hf.co/gammatau/starcoder-1b-fit
Download pytorch_model.bin from gammatau/starcoder-1b-fit: direct link, hf CLI and curl.
- Browser
- Download file 4.55 GB
-
https://huggingface.co/gammatau/starcoder-1b-fit/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://gammatau/starcoder-1b-fit/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gammatau/starcoder-1b-fit/resolve/main/pytorch_model.bin
4.55 GB
- Xet hash:
- 1a13084038dca38e5175efad6175a10cf654d5ee1d67399fb0c42bf5c75abfb1
- Size of remote file:
- 4.55 GB
- SHA256:
- 35b85fd218ff16c4a06aca4c0b6dd3c6db9cbf7b25045c891f2db447c952876b
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