Instructions to use huggingtweets/nfl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use huggingtweets/nfl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="huggingtweets/nfl")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("huggingtweets/nfl") model = AutoModelForCausalLM.from_pretrained("huggingtweets/nfl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use huggingtweets/nfl with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "huggingtweets/nfl" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "huggingtweets/nfl", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/huggingtweets/nfl
- SGLang
How to use huggingtweets/nfl 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 "huggingtweets/nfl" \ --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": "huggingtweets/nfl", "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 "huggingtweets/nfl" \ --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": "huggingtweets/nfl", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use huggingtweets/nfl with Docker Model Runner:
docker model run hf.co/huggingtweets/nfl
Download training_args.bin from huggingtweets/nfl: direct link, hf CLI and curl.
- Browser
- Download file 2.16 kB
-
https://huggingface.co/huggingtweets/nfl/resolve/main/training_args.bin
- Command line
-
hf download hf://huggingtweets/nfl/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/huggingtweets/nfl/resolve/main/training_args.bin
2.16 kB
- Xet hash:
- c49025ac54802710d97dff7eda2ad8a2aa194bf476a6c90e83b061376277c060
- Size of remote file:
- 2.16 kB
- SHA256:
- 5e76364a3528aee0e05f7294b0175e59ba74b1d5ff0a73506a805ac7cf74a317
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