Instructions to use namesarnav/causalbench_code-bert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use namesarnav/causalbench_code-bert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="namesarnav/causalbench_code-bert-base-uncased")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("namesarnav/causalbench_code-bert-base-uncased") model = AutoModelForSequenceClassification.from_pretrained("namesarnav/causalbench_code-bert-base-uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Fine-tuned on causal classification
Browse files- eval_results.json +9 -0
eval_results.json
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{
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"eval_loss": 0.6049319505691528,
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"eval_accuracy": 0.700381679389313,
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"eval_macro_f1": 0.6969616849377582,
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"eval_runtime": 16.6055,
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"eval_samples_per_second": 94.667,
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"eval_steps_per_second": 3.011,
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"epoch": 5.0
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}
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