Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use MarPla/BertDiscussionComp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MarPla/BertDiscussionComp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MarPla/BertDiscussionComp")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MarPla/BertDiscussionComp") model = AutoModelForSequenceClassification.from_pretrained("MarPla/BertDiscussionComp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4daf6e6965a491db8f17c88a4e05776a1986a480cf4b3e28630193e731ab227f
- Size of remote file:
- 438 MB
- SHA256:
- 35ff960c5dded2ad0ec1603a92d33f2c327e4393da3794dcacef1277233aefe0
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