Instructions to use connectivity/feather_berts_56 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_56 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_56")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_56") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_56", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/feather_berts_56: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/feather_berts_56/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/feather_berts_56/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/feather_berts_56/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 63263ec557b2d8c23682cfa650a95807d3e37ad479170f308189a3e9ad05e2bc
- Size of remote file:
- 438 MB
- SHA256:
- f22970ef7819e3b27dfbb104b073b5cac485ff4caa902e7d33103d5f81129663
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