Instructions to use connectivity/feather_berts_58 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_58 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_58")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_58") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_58", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/feather_berts_58: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/feather_berts_58/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/feather_berts_58/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/feather_berts_58/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 38699a055c2dea852e747a88af04296b82613ac2c5bf8cd6680736e907e91564
- Size of remote file:
- 438 MB
- SHA256:
- f5f4d3706efbd520d39364d8230cfe7d37b27126acb6ea904cdf66f711f28ee7
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