Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use MarPla/BertAbstractComp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MarPla/BertAbstractComp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MarPla/BertAbstractComp")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MarPla/BertAbstractComp") model = AutoModelForSequenceClassification.from_pretrained("MarPla/BertAbstractComp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
BertAbstractComp / runs /Jun09_15-13-40_a6a0c55f07b0 /events.out.tfevents.1717946020.a6a0c55f07b0.35.2
- Xet hash:
- 53cee62f8c99feb876461f0a82d691a4b48ce2e944181c282e9b8bf53c4d12ff
- Size of remote file:
- 11.9 kB
- SHA256:
- 02a6a77274d5e8f4489380b2acd15f0ea1cbd09035fa7f982229f6324e54d402
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