Instructions to use connectivity/feather_berts_45 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_45 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_45")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_45") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_45", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download hans_eval_bert_45.json from connectivity/feather_berts_45: direct link, hf CLI and curl.
- Browser
- Download file 12.1 MB
-
https://huggingface.co/connectivity/feather_berts_45/resolve/main/hans_eval_bert_45.json
- Command line
-
hf download hf://connectivity/feather_berts_45/hans_eval_bert_45.json
-
curl -L -o hans_eval_bert_45.json https://huggingface.co/connectivity/feather_berts_45/resolve/main/hans_eval_bert_45.json
12.1 MB
- Xet hash:
- b774a0160b6cc93c4b8cdc093fb5f9c906e1ca7cf6013ad1ec0a4901ea633da5
- Size of remote file:
- 12.1 MB
- SHA256:
- 8bf93b9a92eee1ec3a62eaa8ffd80912066a2c5048e1900f05df8ad41f6d640d
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