Instructions to use FigoMe/news-gpt-neo-1.3B-keywords-line-by-line-reverse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FigoMe/news-gpt-neo-1.3B-keywords-line-by-line-reverse with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="FigoMe/news-gpt-neo-1.3B-keywords-line-by-line-reverse")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("FigoMe/news-gpt-neo-1.3B-keywords-line-by-line-reverse") model = AutoModelForCausalLM.from_pretrained("FigoMe/news-gpt-neo-1.3B-keywords-line-by-line-reverse", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use FigoMe/news-gpt-neo-1.3B-keywords-line-by-line-reverse with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "FigoMe/news-gpt-neo-1.3B-keywords-line-by-line-reverse" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "FigoMe/news-gpt-neo-1.3B-keywords-line-by-line-reverse", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/FigoMe/news-gpt-neo-1.3B-keywords-line-by-line-reverse
- SGLang
How to use FigoMe/news-gpt-neo-1.3B-keywords-line-by-line-reverse 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 "FigoMe/news-gpt-neo-1.3B-keywords-line-by-line-reverse" \ --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": "FigoMe/news-gpt-neo-1.3B-keywords-line-by-line-reverse", "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 "FigoMe/news-gpt-neo-1.3B-keywords-line-by-line-reverse" \ --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": "FigoMe/news-gpt-neo-1.3B-keywords-line-by-line-reverse", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use FigoMe/news-gpt-neo-1.3B-keywords-line-by-line-reverse with Docker Model Runner:
docker model run hf.co/FigoMe/news-gpt-neo-1.3B-keywords-line-by-line-reverse
- Xet hash:
- fca0c3e20a63450e30e54b6b4153046bcd15acee44559d1fb44c8c3f2c174578
- Size of remote file:
- 2.35 kB
- SHA256:
- ef424c13f468059e01d5f06818397eb2475d35b9af476c8d539478d38e025fa2
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