Instructions to use delphi-suite/v0-llama2-800k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use delphi-suite/v0-llama2-800k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="delphi-suite/v0-llama2-800k")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("delphi-suite/v0-llama2-800k") model = AutoModelForCausalLM.from_pretrained("delphi-suite/v0-llama2-800k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use delphi-suite/v0-llama2-800k with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "delphi-suite/v0-llama2-800k" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "delphi-suite/v0-llama2-800k", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/delphi-suite/v0-llama2-800k
- SGLang
How to use delphi-suite/v0-llama2-800k 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 "delphi-suite/v0-llama2-800k" \ --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": "delphi-suite/v0-llama2-800k", "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 "delphi-suite/v0-llama2-800k" \ --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": "delphi-suite/v0-llama2-800k", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use delphi-suite/v0-llama2-800k with Docker Model Runner:
docker model run hf.co/delphi-suite/v0-llama2-800k
Download pytorch_model.bin from delphi-suite/v0-llama2-800k: direct link, hf CLI and curl.
- Browser
- Download file 5.79 MB
-
https://huggingface.co/delphi-suite/v0-llama2-800k/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://delphi-suite/v0-llama2-800k/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/delphi-suite/v0-llama2-800k/resolve/main/pytorch_model.bin
5.79 MB
- Xet hash:
- d4c2a2837d5bae8af2ec08a7356a1284a9d74b59abe4d6c85abff3acb3d443b5
- Size of remote file:
- 5.79 MB
- SHA256:
- 0ee2ebf9a7a57c075d984d32bebfa10dc3cdb5675f07a19d8668f5ece91ba44a
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