Instructions to use connectivity/feather_berts_37 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_37 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_37")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_37") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_37", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/feather_berts_37: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/feather_berts_37/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/feather_berts_37/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/feather_berts_37/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- c26a16d82d21d2aadf17b8b6443294c7763cb4da995bc9fe7ce97d3f76f9ca74
- Size of remote file:
- 438 MB
- SHA256:
- 55b7538514f8cf2b51ec5b9c2273ed6ebee0012ed058398338f4eff8a3e436e3
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