Instructions to use connectivity/feather_berts_97 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_97 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_97")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_97") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_97", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/feather_berts_97: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/feather_berts_97/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/feather_berts_97/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/feather_berts_97/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 3ea1f02e7a73e511b899b2f1a368558a0d90848adf8c3eb336f35144fb0a0759
- Size of remote file:
- 438 MB
- SHA256:
- 2a64c703d9825108df62a5a56f3884e45dbbda29685670ef9885d6d0a833d31f
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