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:
- 19b23c1fa7e705341b943fc205cf785089b0eea2ac23b217ee67406cc56eb89d
- Size of remote file:
- 438 MB
- SHA256:
- 624a489e9117b78b8c4d93a09ea2ea7ea1dc05311bed2deebaf8de692831d813
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