Instructions to use yhavinga/t5-base-36L-dutch-english-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yhavinga/t5-base-36L-dutch-english-cased with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("yhavinga/t5-base-36L-dutch-english-cased") model = AutoModelForMultimodalLM.from_pretrained("yhavinga/t5-base-36L-dutch-english-cased") - Notebooks
- Google Colab
- Kaggle
Saving weights at step 3408k, Loss: 1.051, Acc: 0.757
Browse files- eval_results.json +4 -0
- flax_model.msgpack +1 -1
- opt_state.msgpack +1 -1
- training_state.json +1 -1
eval_results.json
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{
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"eval_accuracy": 0.7573560476303101,
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"eval_loss": 1.0511531829833984
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}
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flax_model.msgpack
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opt_state.msgpack
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oid sha256:f6130a0e8b7596b9930522354255461d7291c808faf20b0fec007c3d73de71c6
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training_state.json
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{"step":
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{"step": 3400001}
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