Instructions to use connectivity/feather_berts_69 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_69 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_69")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_69") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_69", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/feather_berts_69: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/feather_berts_69/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/feather_berts_69/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/feather_berts_69/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 07ab3df52038307c8d397ee98969f17976af59d117e1d65c83b8ba5f2b4f6654
- Size of remote file:
- 438 MB
- SHA256:
- c6bd4be63f2912f47129aefcf37f7f3437a5fefd37c957d7bcc7a049c76d038a
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