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:
- 43d937f4f5955cdcf2653358870b4bdc7f3e7ed622cbb3d8a70b64d3699d97f2
- Size of remote file:
- 5.11 kB
- SHA256:
- 495f480c12b36a5a6b7afe8e3efc03e998017fab563987eaa38b20ed6cf8aeed
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