Instructions to use connectivity/feather_berts_97 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_97 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_97")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_97") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_97", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download hans_eval_bert_97.json from connectivity/feather_berts_97: direct link, hf CLI and curl.
- Browser
- Download file 12.1 MB
-
https://huggingface.co/connectivity/feather_berts_97/resolve/main/hans_eval_bert_97.json
- Command line
-
hf download hf://connectivity/feather_berts_97/hans_eval_bert_97.json
-
curl -L -o hans_eval_bert_97.json https://huggingface.co/connectivity/feather_berts_97/resolve/main/hans_eval_bert_97.json
12.1 MB
- Xet hash:
- 82d943dacdf96db240b7207b4431941cf6a88b629731c2a9465492547d96b200
- Size of remote file:
- 12.1 MB
- SHA256:
- 6e0d70284d2605a3e783f2a371abed348a225ecb3a0536116e477a75001deea5
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