Instructions to use connectivity/feather_berts_46 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_46 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_46")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_46") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_46", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/feather_berts_46: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/feather_berts_46/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/feather_berts_46/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/feather_berts_46/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 616a554f873a8bda82940c1d5c741a7397ea8b5c124a46df5377250f73516d8e
- Size of remote file:
- 438 MB
- SHA256:
- 0432c2a4b988fdc003d41ca78087fbd56f74e7c4413b741c9517b9d380917b4c
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