Instructions to use moneim/intent-bart-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moneim/intent-bart-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="moneim/intent-bart-mnli")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("moneim/intent-bart-mnli") model = AutoModelForSequenceClassification.from_pretrained("moneim/intent-bart-mnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Initial BART-MNLI intent fine-tune
Browse files
README.md
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This model is a fine-tuned version of [facebook/bart-large-mnli](https://huggingface.co/facebook/bart-large-mnli) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy:
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## Model description
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This model is a fine-tuned version of [facebook/bart-large-mnli](https://huggingface.co/facebook/bart-large-mnli) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0000
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- Accuracy: 1.0
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## Model description
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