Instructions to use eclec/patentClassfication3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eclec/patentClassfication3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="eclec/patentClassfication3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("eclec/patentClassfication3") model = AutoModelForSequenceClassification.from_pretrained("eclec/patentClassfication3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from eclec/patentClassfication3: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/eclec/patentClassfication3/resolve/6f0c345ee221ad513bc09745ddf8b8a8dd020d9a/training_args.bin
- Command line
-
hf download hf://eclec/patentClassfication3@6f0c345ee221ad513bc09745ddf8b8a8dd020d9a/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/eclec/patentClassfication3/resolve/6f0c345ee221ad513bc09745ddf8b8a8dd020d9a/training_args.bin
3.96 kB
- Xet hash:
- 15327d6bd81ab5bd4d6848fb8b6636c52628b345b35e815c8f2578fbd03dc9a2
- Size of remote file:
- 3.96 kB
- SHA256:
- 201bafcb6d7b605aede06703b7fd037d0b96d771d6608573459519f3c7936369
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