Instructions to use connectivity/feather_berts_13 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_13 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_13")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_13") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_13", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download hans_eval_bert_13.json from connectivity/feather_berts_13: direct link, hf CLI and curl.
- Browser
- Download file 12.1 MB
-
https://huggingface.co/connectivity/feather_berts_13/resolve/main/hans_eval_bert_13.json
- Command line
-
hf download hf://connectivity/feather_berts_13/hans_eval_bert_13.json
-
curl -L -o hans_eval_bert_13.json https://huggingface.co/connectivity/feather_berts_13/resolve/main/hans_eval_bert_13.json
12.1 MB
- Xet hash:
- 016448eb00861a02f43a6d1b3eafefd3b7adb818963d8ee6ab5827f2e3b0ce9f
- Size of remote file:
- 12.1 MB
- SHA256:
- db129a307f7c45c163bca70ca133a403da965f3377b5d044167234339d652ed0
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