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/6f0c345ee221ad513bc09745ddf8b8a8dd020d9a/pytorch_model.bin
- Command line
-
hf download hf://eclec/patentClassfication3@6f0c345ee221ad513bc09745ddf8b8a8dd020d9a/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/eclec/patentClassfication3/resolve/6f0c345ee221ad513bc09745ddf8b8a8dd020d9a/pytorch_model.bin
1.74 GB
- Xet hash:
- 93a6f2b4a0ed13e8f6fd0c38f7d3380c0f41ae6a61b5373c0960f74df375e5b4
- Size of remote file:
- 1.74 GB
- SHA256:
- c9234e261bb65b814fa45e8376d94a4219209e47a4b22bfad2aa6e378fd72938
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