Instructions to use connectivity/feather_berts_55 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_55 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_55")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_55") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_55", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/feather_berts_55: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/feather_berts_55/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/feather_berts_55/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/feather_berts_55/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 6088c744084a02d9e993e4ef70f0353680ad5ea49eee60412e0d8ba67f60682a
- Size of remote file:
- 438 MB
- SHA256:
- 08d20b93c13ba8ecc3c84cd0ad6e55a456bc4e54a9f2d9e4a77d9503b2683e16
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