Text Generation
Transformers
PyTorch
TensorBoard
gpt2
Generated from Trainer
text-generation-inference
Instructions to use kuttersn/test-clm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kuttersn/test-clm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="kuttersn/test-clm")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("kuttersn/test-clm") model = AutoModelForCausalLM.from_pretrained("kuttersn/test-clm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use kuttersn/test-clm with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "kuttersn/test-clm" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "kuttersn/test-clm", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/kuttersn/test-clm
- SGLang
How to use kuttersn/test-clm 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 "kuttersn/test-clm" \ --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": "kuttersn/test-clm", "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 "kuttersn/test-clm" \ --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": "kuttersn/test-clm", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use kuttersn/test-clm with Docker Model Runner:
docker model run hf.co/kuttersn/test-clm
Download training_args.bin from kuttersn/test-clm: direct link, hf CLI and curl.
- Browser
- Download file 3.31 kB
-
https://huggingface.co/kuttersn/test-clm/resolve/main/training_args.bin
- Command line
-
hf download hf://kuttersn/test-clm/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/kuttersn/test-clm/resolve/main/training_args.bin
3.31 kB
- Xet hash:
- ba33b6f2300fd2a63e12afd0d367d2b05beb3607ff35a6eb1ae61b49713dd5e3
- Size of remote file:
- 3.31 kB
- SHA256:
- 7e84b0e27e68fb5f96af8cd1b47ab3804c1b6b978a7f467601ef4463bee14e4e
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