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:
- 6aa57a92e12ea5e59774e9c446c0eb443d653eb2f9c1919f6d86b090f7b90e69
- Size of remote file:
- 5.3 kB
- SHA256:
- 10c4fa272805d35736836a3e009621bd76996807c65d9d36c3031044a285f570
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