Instructions to use connectivity/feather_berts_63 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_63 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_63")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_63") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_63", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download hans_eval_bert_63.json from connectivity/feather_berts_63: direct link, hf CLI and curl.
- Browser
- Download file 12.1 MB
-
https://huggingface.co/connectivity/feather_berts_63/resolve/main/hans_eval_bert_63.json
- Command line
-
hf download hf://connectivity/feather_berts_63/hans_eval_bert_63.json
-
curl -L -o hans_eval_bert_63.json https://huggingface.co/connectivity/feather_berts_63/resolve/main/hans_eval_bert_63.json
12.1 MB
- Xet hash:
- 30daa0e1e2c1dd594f675543c7fcbed84beb18954888965b37b25ff29530e5ea
- Size of remote file:
- 12.1 MB
- SHA256:
- c6ec45c126c6412a8d53f37c51f378d18788995f3f2ebf61b78523af22f8dc1c
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