Instructions to use cfpark00/gpt2_cube_v2-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cfpark00/gpt2_cube_v2-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="cfpark00/gpt2_cube_v2-2", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("cfpark00/gpt2_cube_v2-2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use cfpark00/gpt2_cube_v2-2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "cfpark00/gpt2_cube_v2-2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "cfpark00/gpt2_cube_v2-2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/cfpark00/gpt2_cube_v2-2
- SGLang
How to use cfpark00/gpt2_cube_v2-2 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 "cfpark00/gpt2_cube_v2-2" \ --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": "cfpark00/gpt2_cube_v2-2", "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 "cfpark00/gpt2_cube_v2-2" \ --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": "cfpark00/gpt2_cube_v2-2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use cfpark00/gpt2_cube_v2-2 with Docker Model Runner:
docker model run hf.co/cfpark00/gpt2_cube_v2-2
Download tokenizer.json from cfpark00/gpt2_cube_v2-2: direct link, hf CLI and curl.
- Browser
- Download file 739 Bytes
-
https://huggingface.co/cfpark00/gpt2_cube_v2-2/resolve/main/tokenizer.json
- Command line
-
hf download hf://cfpark00/gpt2_cube_v2-2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/cfpark00/gpt2_cube_v2-2/resolve/main/tokenizer.json
739 Bytes
| { | |
| "version": "1.0", | |
| "truncation": null, | |
| "padding": null, | |
| "added_tokens": [ | |
| { | |
| "id": 15, | |
| "content": "<|endoftext|>", | |
| "single_word": false, | |
| "lstrip": false, | |
| "rstrip": false, | |
| "normalized": false, | |
| "special": true | |
| } | |
| ], | |
| "normalizer": null, | |
| "pre_tokenizer": { | |
| "type": "Whitespace" | |
| }, | |
| "post_processor": null, | |
| "decoder": null, | |
| "model": { | |
| "type": "WordLevel", | |
| "vocab": { | |
| "r": 0, | |
| "u": 1, | |
| "f": 2, | |
| "l": 3, | |
| "d": 4, | |
| "b": 5, | |
| "R": 6, | |
| "RR": 7, | |
| "RRR": 8, | |
| "U": 9, | |
| "UU": 10, | |
| "UUU": 11, | |
| "F": 12, | |
| "FF": 13, | |
| "FFF": 14, | |
| "<|endoftext|>": 15 | |
| }, | |
| "unk_token": "<|endoftext|>" | |
| } | |
| } |