Instructions to use connectivity/feather_berts_89 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_89 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_89")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_89") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_89", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download hans_eval_bert_89.json from connectivity/feather_berts_89: direct link, hf CLI and curl.
- Browser
- Download file 12.1 MB
-
https://huggingface.co/connectivity/feather_berts_89/resolve/main/hans_eval_bert_89.json
- Command line
-
hf download hf://connectivity/feather_berts_89/hans_eval_bert_89.json
-
curl -L -o hans_eval_bert_89.json https://huggingface.co/connectivity/feather_berts_89/resolve/main/hans_eval_bert_89.json
12.1 MB
- Xet hash:
- 06befd6a123bdc48a566a7ecd249d5fdbf1ac01f8c6cdb7113f01a98c079af33
- Size of remote file:
- 12.1 MB
- SHA256:
- c89254377ed82e5198c16511d9905a0181b3a649c8b4b252c6eced6053015e07
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