Instructions to use connectivity/feather_berts_90 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_90 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_90")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_90") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_90", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/feather_berts_90: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/feather_berts_90/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/feather_berts_90/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/feather_berts_90/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 3e6e2a7b0aca6e5e297bc334f41da02e3abae9402f07eb5345d5114b14603674
- Size of remote file:
- 438 MB
- SHA256:
- 116945546c90e367b8f89e86c7abc487b36efb1f9b8e3e999b9e2b9427459178
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