Instructions to use Ethlake/testllava with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ethlake/testllava with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="Ethlake/testllava")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Ethlake/testllava") model = AutoModelForMultimodalLM.from_pretrained("Ethlake/testllava") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Ethlake/testllava with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Ethlake/testllava" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Ethlake/testllava", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Ethlake/testllava
- SGLang
How to use Ethlake/testllava 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 "Ethlake/testllava" \ --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": "Ethlake/testllava", "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 "Ethlake/testllava" \ --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": "Ethlake/testllava", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Ethlake/testllava with Docker Model Runner:
docker model run hf.co/Ethlake/testllava
| { | |
| "architectures": [ | |
| "LlavaForConditionalGeneration" | |
| ], | |
| "ignore_index": -100, | |
| "image_token_id": 32000, | |
| "image_token_index": 32000, | |
| "model_type": "llava", | |
| "pad_token_id": 32001, | |
| "projector_hidden_act": "gelu", | |
| "text_config": { | |
| "_name_or_path": "lmsys/vicuna-7b-v1.5", | |
| "architectures": [ | |
| "LlamaForCausalLM" | |
| ], | |
| "max_position_embeddings": 4096, | |
| "model_type": "llama", | |
| "pad_token_id": 0, | |
| "rms_norm_eps": 1e-05, | |
| "torch_dtype": "float16", | |
| "vocab_size": 32064 | |
| }, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.37.2", | |
| "vision_config": { | |
| "hidden_size": 1024, | |
| "image_size": 336, | |
| "intermediate_size": 4096, | |
| "model_type": "clip_vision_model", | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 24, | |
| "patch_size": 14, | |
| "projection_dim": 768, | |
| "vocab_size": 32000 | |
| }, | |
| "vision_feature_layer": -2, | |
| "vision_feature_select_strategy": "default", | |
| "vocab_size": 32064 | |
| } | |