Instructions to use YituTech/conv-bert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YituTech/conv-bert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="YituTech/conv-bert-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("YituTech/conv-bert-base") model = AutoModel.from_pretrained("YituTech/conv-bert-base") - Inference
- Notebooks
- Google Colab
- Kaggle
Create README.md
Browse files
README.md
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---
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license: apache-2.0
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datasets:
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- nvidia/ChatQA-Training-Data
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- HuggingFaceFW/fineweb
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language:
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- am
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metrics:
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- accuracy
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- character
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library_name: fastai
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pipeline_tag: image-to-3d
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---
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