Instructions to use connectivity/feather_berts_85 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_85 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_85")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_85") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_85", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/feather_berts_85: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/feather_berts_85/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/feather_berts_85/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/feather_berts_85/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- c453283c3d5953ceb49288d4a44bd348d6225597d7beb0dc6463ffe4684a374c
- Size of remote file:
- 438 MB
- SHA256:
- 53b504752e8afea22e1f7ef6ff56ad4d1addc527cf53bd13b2a45a40cbb8e577
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