Instructions to use SALT-NLP/LLaVAR_delta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SALT-NLP/LLaVAR_delta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="SALT-NLP/LLaVAR_delta")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCausalLM processor = AutoProcessor.from_pretrained("SALT-NLP/LLaVAR_delta") model = AutoModelForCausalLM.from_pretrained("SALT-NLP/LLaVAR_delta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use SALT-NLP/LLaVAR_delta with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SALT-NLP/LLaVAR_delta" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SALT-NLP/LLaVAR_delta", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/SALT-NLP/LLaVAR_delta
- SGLang
How to use SALT-NLP/LLaVAR_delta 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 "SALT-NLP/LLaVAR_delta" \ --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": "SALT-NLP/LLaVAR_delta", "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 "SALT-NLP/LLaVAR_delta" \ --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": "SALT-NLP/LLaVAR_delta", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use SALT-NLP/LLaVAR_delta with Docker Model Runner:
docker model run hf.co/SALT-NLP/LLaVAR_delta
Commit History
-
Upload llavar-13b-pretrain.bin with huggingface_hub
a2b88da
-
Update README.md
945d7d0
-
Update readme
02cb409 -
Init README.md
e74e0cb -
Upload tokenizer.model with huggingface_hub
45883bf -
Upload tokenizer_config.json with huggingface_hub
0e64cd3 -
Upload special_tokens_map.json with huggingface_hub
c7d1a94 -
Upload pytorch_model.bin.index.json with huggingface_hub
a7cf50a -
Upload pytorch_model-00003-of-00003.bin with huggingface_hub
757190c -
Upload pytorch_model-00002-of-00003.bin with huggingface_hub
2bb3c3e -
Upload generation_config.json with huggingface_hub
1f2272a -
Upload config.json with huggingface_hub
c340cb6 -
Upload added_tokens.json with huggingface_hub
4e5ef55 -
Upload pytorch_model-00001-of-00003.bin with huggingface_hub
a27430d -
initial commit
6e2e8fc