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 pytorch_model.bin from eclec/patentClassfication3: direct link, hf CLI and curl.
- Browser
- Download file 1.74 GB
-
https://huggingface.co/eclec/patentClassfication3/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://eclec/patentClassfication3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/eclec/patentClassfication3/resolve/main/pytorch_model.bin
1.74 GB
- Xet hash:
- b2e3be7196ff1745390d76bacae4d02c0493a4ef35cdea7e242d05c864654967
- Size of remote file:
- 1.74 GB
- SHA256:
- 236a5bc55175d8521186080cf3eb320ac811079112c181b1470715175c30f171
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