Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use eskayML/old_bert_pytranscripts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eskayML/old_bert_pytranscripts with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="eskayML/old_bert_pytranscripts")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("eskayML/old_bert_pytranscripts") model = AutoModelForSequenceClassification.from_pretrained("eskayML/old_bert_pytranscripts") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0cc4390b930655dfbe701c75766468a5b62faac4f1dacf227d57ae34b3fa8bc8
- Size of remote file:
- 268 MB
- SHA256:
- f1b56d9adec1afdce7de487850451b6072e8b37d8da461e2acafdeccd6065eb4
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