Instructions to use connectivity/feather_berts_50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_50 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_50")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_50") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_50", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/feather_berts_50: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/feather_berts_50/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/feather_berts_50/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/feather_berts_50/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 615bf9db6b1bdd4fa4d52d03a66861f151e21821271c9a29c441f59d526f5d6a
- Size of remote file:
- 438 MB
- SHA256:
- edec5da4d35a7013bfbdc3b35abbf57a07ffaf51a5774d3eaa6277b89b736f53
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