Instructions to use hf-internal-testing/tiny-random-UdopModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-UdopModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-UdopModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-UdopModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-UdopModel") - Notebooks
- Google Colab
- Kaggle
Update tiny models for UdopModel
Browse files- model.safetensors +1 -1
- tokenizer_config.json +1 -1
model.safetensors
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version https://git-lfs.github.com/spec/v1
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version https://git-lfs.github.com/spec/v1
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oid sha256:e3940c357b57a870f78ffd2ea4f2b27bbc43dbab4751df760a572e1c0576cf41
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size 4829464
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tokenizer_config.json
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"clean_up_tokenization_spaces": true,
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"eos_token": "</s>",
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"legacy": true,
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"model_max_length":
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"only_label_first_subword": true,
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"pad_token": "<pad>",
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"pad_token_box": [
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"clean_up_tokenization_spaces": true,
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"eos_token": "</s>",
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"legacy": true,
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"model_max_length": 1000000000000000019884624838656,
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"only_label_first_subword": true,
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"pad_token": "<pad>",
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"pad_token_box": [
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