Text Classification
Transformers
PyTorch
Safetensors
English
bert
disfluency identification
text-embeddings-inference
Instructions to use 4i-ai/BERT_disfluency_cls with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 4i-ai/BERT_disfluency_cls with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="4i-ai/BERT_disfluency_cls")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("4i-ai/BERT_disfluency_cls") model = AutoModelForSequenceClassification.from_pretrained("4i-ai/BERT_disfluency_cls", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from 4i-ai/BERT_disfluency_cls: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/4i-ai/BERT_disfluency_cls/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://4i-ai/BERT_disfluency_cls/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/4i-ai/BERT_disfluency_cls/resolve/main/pytorch_model.bin
433 MB
- Xet hash:
- 4becc9aab7be347a7dbd8fea57c17f5c29ac010772a8cadac236f4463fa646d2
- Size of remote file:
- 433 MB
- SHA256:
- e8a42457ff4c4ec18021fa483036e31b694bdf9e0293034becb02be6277907c7
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