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/refs%2Fpr%2F2/training_args.bin
- Command line
-
hf download hf://eclec/patentClassfication3@refs/pr/2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/eclec/patentClassfication3/resolve/refs%2Fpr%2F2/training_args.bin
3.96 kB
- Xet hash:
- 81de50b47a8221834a9ee7a718bd721c8b012430dedb8f5aebeb4e714581a485
- Size of remote file:
- 3.96 kB
- SHA256:
- c60396f730adf44ab39655a665831e3873f6fe1278845f729fa3221e5e14fc5d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.