Instructions to use connectivity/feather_berts_48 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_48 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_48")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_48") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_48", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/feather_berts_48: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/feather_berts_48/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/feather_berts_48/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/feather_berts_48/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- c867908ce756770f1c0863857836bc55e4d9f347316f67178c803026a195162f
- Size of remote file:
- 438 MB
- SHA256:
- bb9e76568a04eaaf69b6272de286835100e68679ed5b58f85e0829b3f1d35cf5
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