Instructions to use nvlan/ndc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvlan/ndc with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nvlan/ndc", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use nvlan/ndc with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for nvlan/ndc to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for nvlan/ndc to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for nvlan/ndc to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="nvlan/ndc", max_seq_length=2048, )
Upload model trained with Unsloth
Browse filesUpload model trained with Unsloth 2x faster
- preprocessor_config.json +1 -1
- tokenizer.json +2 -2
- tokenizer_config.json +1 -1
- video_preprocessor_config.json +1 -1
preprocessor_config.json
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"patch_size": 16,
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"processor_class": "Qwen3VLProcessor",
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"resample": 3,
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"rescale_factor": 0.00392156862745098,
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"return_tensors": null,
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tokenizer.json
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size 11422654
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tokenizer_config.json
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"model_max_length": 262144,
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"pad_token": "<|vision_pad|>",
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"padding_side": "right",
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"processor_class": "
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"split_special_tokens": false,
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"tokenizer_class": "Qwen2Tokenizer",
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"model_max_length": 262144,
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"pad_token": "<|vision_pad|>",
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"padding_side": "right",
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"processor_class": "Qwen3VLProcessor",
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"split_special_tokens": false,
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"tokenizer_class": "Qwen2Tokenizer",
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"unk_token": null
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video_preprocessor_config.json
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"num_frames": null,
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"pad_size": null,
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"patch_size": 16,
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"processor_class": "
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"resample": 3,
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"rescale_factor": 0.00392156862745098,
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"return_metadata": false,
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"num_frames": null,
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"pad_size": null,
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"patch_size": 16,
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"processor_class": "Qwen3VLProcessor",
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"resample": 3,
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"rescale_factor": 0.00392156862745098,
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"return_metadata": false,
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