Instructions to use Gege24/augmented-230dbcbeabf544be with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gege24/augmented-230dbcbeabf544be with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Gege24/augmented-230dbcbeabf544be")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Gege24/augmented-230dbcbeabf544be") model = AutoModelForCausalLM.from_pretrained("Gege24/augmented-230dbcbeabf544be") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Gege24/augmented-230dbcbeabf544be with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Gege24/augmented-230dbcbeabf544be" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Gege24/augmented-230dbcbeabf544be", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Gege24/augmented-230dbcbeabf544be
- SGLang
How to use Gege24/augmented-230dbcbeabf544be 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 "Gege24/augmented-230dbcbeabf544be" \ --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": "Gege24/augmented-230dbcbeabf544be", "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 "Gege24/augmented-230dbcbeabf544be" \ --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": "Gege24/augmented-230dbcbeabf544be", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Gege24/augmented-230dbcbeabf544be with Docker Model Runner:
docker model run hf.co/Gege24/augmented-230dbcbeabf544be
| { | |
| "add_prefix_space": false, | |
| "backend": "tokenizers", | |
| "bos_token": "<|endoftext|>", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|endoftext|>", | |
| "errors": "replace", | |
| "extra_special_tokens": [ | |
| "<|endoftext|>", | |
| "<|im_start|>", | |
| "<|im_end|>", | |
| "<repo_name>", | |
| "<reponame>", | |
| "<file_sep>", | |
| "<filename>", | |
| "<gh_stars>", | |
| "<issue_start>", | |
| "<issue_comment>", | |
| "<issue_closed>", | |
| "<jupyter_start>", | |
| "<jupyter_text>", | |
| "<jupyter_code>", | |
| "<jupyter_output>", | |
| "<jupyter_script>", | |
| "<empty_output>" | |
| ], | |
| "is_local": false, | |
| "local_files_only": false, | |
| "model_max_length": 8192, | |
| "pad_token": "<|PAD_TOKEN|>", | |
| "padding_side": "left", | |
| "tokenizer_class": "GPT2Tokenizer", | |
| "unk_token": "�", | |
| "vocab_size": 49152 | |
| } | |