Question Answering
Adapters
English
falcon
QLoRA
Adapters
llms
Transformers
Fine-Tuning
PEFT
SFTTrainer
Open-Source
LoRA
Attention
code
Falcon-7b
custom_code
Instructions to use avnishkr/falcon-QAMaster with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use avnishkr/falcon-QAMaster with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("<base-model-id>") model.load_adapter("avnishkr/falcon-QAMaster", set_active=True) - Notebooks
- Google Colab
- Kaggle
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# 🚀 Falcon-7b-QueAns Falcon-7b-QueAns is a chatbot-like model for Question and Answering. It was built by fine-tuning [Falcon-7B](https://huggingface.co/tiiuae/falcon-7b) on the [SQuAD](https://huggingface.co/datasets/squad) dataset. This repo only includes the QLoRA adapters from fine-tuning with 🤗's [peft](https://github.com/huggingface/peft) package. ## Model Summary - **Model Type:** Causal decoder-only - **Language(s):** English - **Base Model:** Falcon-7B (License: Apache 2.0) - **Datasets:** [SQuAD](https://huggingface.co/datasets/squad) (License: cc-by-4.0), [Adversarial_qa](https://huggingface.co/datasets/adversarial_qa) (License: cc-by-sa-4.0) - **License(s):** Apache 2.0 inherited from "Base Model" and "Datasets" ## Why use Falcon-7B? * **It outperforms comparable open-source models** (e.g., [MPT-7B](https://huggingface.co/mosaicml/mpt-7b), [StableLM](https://github.com/Stability-AI/StableLM), [RedPajama](https://huggingface.co/togethercomputer/RedPajama-INCITE-Base…f6f05a1
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