Instructions to use 0mij/llama-dblp-kgtext with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 0mij/llama-dblp-kgtext with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="0mij/llama-dblp-kgtext")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("0mij/llama-dblp-kgtext") model = AutoModelForCausalLM.from_pretrained("0mij/llama-dblp-kgtext", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use 0mij/llama-dblp-kgtext with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "0mij/llama-dblp-kgtext" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "0mij/llama-dblp-kgtext", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/0mij/llama-dblp-kgtext
- SGLang
How to use 0mij/llama-dblp-kgtext 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 "0mij/llama-dblp-kgtext" \ --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": "0mij/llama-dblp-kgtext", "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 "0mij/llama-dblp-kgtext" \ --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": "0mij/llama-dblp-kgtext", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use 0mij/llama-dblp-kgtext with Docker Model Runner:
docker model run hf.co/0mij/llama-dblp-kgtext
- Xet hash:
- 786efdc3d2f261cc147bc98db23720553f92a382081c9945a41ee3297226c35f
- Size of remote file:
- 315 MB
- SHA256:
- 98e32ac4a0ca047916da3376ef09177fa7860c9f68aea8054e58e693ba88a6f2
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