Instructions to use lifeofcoding/bloom-3b-lora-qa-squadv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use lifeofcoding/bloom-3b-lora-qa-squadv2 with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("fill-in-model-name") model.load_adapter("lifeofcoding/bloom-3b-lora-qa-squadv2", set_active=True) - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 806ede6
Create README.md
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README.md
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---
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license: apache-2.0
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datasets:
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- squad_v2
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---
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# Bloom 3B LoRa QA Squad v2
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This is a LoRa from base model bigscience/bloom-3b trained on squad_v2 for question and answering.
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- **Developed by:** LifeOfCoding
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- **Model type:** LoRa
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- **Finetuned from model:** bigscience/bloom-3b
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## Uses
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Question and answering
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### Direct Use
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Text Generation
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