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_14-47-39_a6a0c55f07b0 /events.out.tfevents.1717944460.a6a0c55f07b0.35.1
- Xet hash:
- ab9f10740abd7ffac0113f64698e33e56482e7700b939e4e6aab592968a89619
- Size of remote file:
- 7.13 kB
- SHA256:
- e384f9301129289f019b0e6e29a74cdf22534ff8cf89a1abfa58e602cc0a57a5
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