Instructions to use connectivity/feather_berts_85 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_85 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_85")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_85") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_85", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download hans_eval_bert_85.json from connectivity/feather_berts_85: direct link, hf CLI and curl.
- Browser
- Download file 12.1 MB
-
https://huggingface.co/connectivity/feather_berts_85/resolve/main/hans_eval_bert_85.json
- Command line
-
hf download hf://connectivity/feather_berts_85/hans_eval_bert_85.json
-
curl -L -o hans_eval_bert_85.json https://huggingface.co/connectivity/feather_berts_85/resolve/main/hans_eval_bert_85.json
12.1 MB
- Xet hash:
- 0d296f5e9d87b3ec8f6a3edd1a6094a209614c4cd1037abc8456a446cbe97193
- Size of remote file:
- 12.1 MB
- SHA256:
- 72e60cbbf4a35ff37bbb372dbf642602263b743e3097ab604bf97998fc16d371
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