Instructions to use tahaman/DamagedCarModelNew with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tahaman/DamagedCarModelNew with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="tahaman/DamagedCarModelNew", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("tahaman/DamagedCarModelNew", trust_remote_code=True) model = AutoModelForMultimodalLM.from_pretrained("tahaman/DamagedCarModelNew", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use tahaman/DamagedCarModelNew with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "tahaman/DamagedCarModelNew" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tahaman/DamagedCarModelNew", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/tahaman/DamagedCarModelNew
- SGLang
How to use tahaman/DamagedCarModelNew 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 "tahaman/DamagedCarModelNew" \ --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": "tahaman/DamagedCarModelNew", "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 "tahaman/DamagedCarModelNew" \ --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": "tahaman/DamagedCarModelNew", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use tahaman/DamagedCarModelNew with Docker Model Runner:
docker model run hf.co/tahaman/DamagedCarModelNew
Update config.json
Browse files- config.json +1 -0
config.json
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"torch_dtype": "float32",
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"transformers_version": "4.41.2",
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"vision_config": {
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"_name_or_path": "",
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"add_cross_attention": false,
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"architectures": null,
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"torch_dtype": "float32",
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"transformers_version": "4.41.2",
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"vision_config": {
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"model_type": "davit",
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"_name_or_path": "",
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"add_cross_attention": false,
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"architectures": null,
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