Instructions to use connectivity/feather_berts_33 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_33 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_33")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_33") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_33", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download hans_eval_bert_33.json from connectivity/feather_berts_33: direct link, hf CLI and curl.
- Browser
- Download file 12.1 MB
-
https://huggingface.co/connectivity/feather_berts_33/resolve/main/hans_eval_bert_33.json
- Command line
-
hf download hf://connectivity/feather_berts_33/hans_eval_bert_33.json
-
curl -L -o hans_eval_bert_33.json https://huggingface.co/connectivity/feather_berts_33/resolve/main/hans_eval_bert_33.json
12.1 MB
- Xet hash:
- 3bf16714e035258219831cf05c8b147392370aad6af26cf1795ad3695153e1a5
- Size of remote file:
- 12.1 MB
- SHA256:
- 036b9ca76edbaa468981be6c4b172b08eb19141f8eaa9f15b4e0f4c6af936483
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