Instructions to use connectivity/feather_berts_8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_8")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_8") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download hans_eval_bert_8.json from connectivity/feather_berts_8: direct link, hf CLI and curl.
- Browser
- Download file 12.1 MB
-
https://huggingface.co/connectivity/feather_berts_8/resolve/main/hans_eval_bert_8.json
- Command line
-
hf download hf://connectivity/feather_berts_8/hans_eval_bert_8.json
-
curl -L -o hans_eval_bert_8.json https://huggingface.co/connectivity/feather_berts_8/resolve/main/hans_eval_bert_8.json
12.1 MB
- Xet hash:
- f0714669a544a76b78f14e7670565cba33a85ff21e6f318c2f5163e638a35254
- Size of remote file:
- 12.1 MB
- SHA256:
- fbf3b398f712e859ea45e795c5c3e12c5a1976fc2425e187444c9b1b37b25785
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