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:
- c0c4bed0fe4d42f4674687b06451f8e67cdcbed2a9df7d8b279ca40afb49a2c4
- Size of remote file:
- 438 MB
- SHA256:
- b228887c64a42d9672d0e00a02dd2ec7216b0aeebe8708bc0abdad8de7f70031
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