Instructions to use connectivity/feather_berts_87 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_87 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_87")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_87") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_87", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download hans_eval_bert_87.json from connectivity/feather_berts_87: direct link, hf CLI and curl.
- Browser
- Download file 12.1 MB
-
https://huggingface.co/connectivity/feather_berts_87/resolve/main/hans_eval_bert_87.json
- Command line
-
hf download hf://connectivity/feather_berts_87/hans_eval_bert_87.json
-
curl -L -o hans_eval_bert_87.json https://huggingface.co/connectivity/feather_berts_87/resolve/main/hans_eval_bert_87.json
12.1 MB
- Xet hash:
- 88f3df9afd2c44f7a485b95f1fbf05e628fde859ffe9e02d53255aa907c15204
- Size of remote file:
- 12.1 MB
- SHA256:
- 214b8bef3cc8d6dd658d1aa1a9fb015fa0d0495c1515889b9a0a2388687b36b6
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