Instructions to use tatsu-lab/alpaca-7b-wdiff with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tatsu-lab/alpaca-7b-wdiff with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="tatsu-lab/alpaca-7b-wdiff")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("tatsu-lab/alpaca-7b-wdiff") model = AutoModelForCausalLM.from_pretrained("tatsu-lab/alpaca-7b-wdiff", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use tatsu-lab/alpaca-7b-wdiff with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "tatsu-lab/alpaca-7b-wdiff" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tatsu-lab/alpaca-7b-wdiff", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/tatsu-lab/alpaca-7b-wdiff
- SGLang
How to use tatsu-lab/alpaca-7b-wdiff 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 "tatsu-lab/alpaca-7b-wdiff" \ --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": "tatsu-lab/alpaca-7b-wdiff", "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 "tatsu-lab/alpaca-7b-wdiff" \ --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": "tatsu-lab/alpaca-7b-wdiff", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use tatsu-lab/alpaca-7b-wdiff with Docker Model Runner:
docker model run hf.co/tatsu-lab/alpaca-7b-wdiff
- Xet hash:
- 95d6a74c3b66e9c1f59b6e5f185b9e5d6f2ea0098dfa0ba979ee442f69cd39cd
- Size of remote file:
- 7.18 GB
- SHA256:
- 6f04361aac986bd6031b5f6ae8db2af30cb2e7edd792d9c1ee4074e47c9608eb
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