bart qg finetune squad

Providermghan3624
Categorydocument-question-answering
Licenseapache-2.0
Downloads89
Stars0

Overview

The bart-qg-finetune-squad model is a specialized encoder-decoder architecture optimized for question generation (QG) based on the SQuAD dataset. Unlike general-purpose LLMs, this model is purpose-built to transform a given context and answer pair into a natural language question. For developers building RAG pipelines or automated educational tools, this model provides a lightweight alternative for generating synthetic training data or creating automated assessments without the latency of massive frontier models. It integrates easily into standard Hugging Face pipelines, offering a predictable output format suitable for downstream NLP tasks where precision in question phrasing is critical.

Highlights

  • Optimized for high-accuracy question generation from context
  • Fine-tuned on the industry-standard SQuAD dataset
  • Lightweight architecture ensures low inference latency
  • Apache-2.0 license allows for flexible commercial deployment
  • Seamless integration with Hugging Face Transformers library

Usage

Install
# Install Hugging Face transformers
pip install transformers torch
SDK Usage
# Load model with transformers
from transformers import AutoModel, AutoTokenizer

model = AutoModel.from_pretrained("mghan3624/bart_qg_finetune_squad")
tokenizer = AutoTokenizer.from_pretrained("mghan3624/bart_qg_finetune_squad")

Hugging Face Download

We recommend downloading the model via the Hugging Face CLI or Hub SDK.

Guidance：Before downloading, install huggingface_hub with:

Guidance 
pip install -U huggingface_hub

CLI Download

Download the full repository

Download the full repository 
huggingface-cli download mghan3624/bart_qg_finetune_squad

Download a single file to a local folder (e.g. config.json into ./dir)

Download a single file to a local folder (e.g. config.json into ./dir) 
huggingface-cli download mghan3624/bart_qg_finetune_squad config.json --local-dir ./dir

See the official docs for more CLI options

SDK Download

SDK Download 
# 模型下载
from huggingface_hub import snapshot_download
model_dir = snapshot_download('mghan3624/bart_qg_finetune_squad')

Git Download

Make sure git-lfs is installed first

Git Download 
git lfs install
git clone https://huggingface.co/mghan3624/bart_qg_finetune_squad

To skip LFS large-file downloads, use:

Skip LFS 
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/mghan3624/bart_qg_finetune_squad

Model files are hosted on the Hugging Face Hub — download directly via HF CLI / SDK / Git, not through this site.

PyTorch / Transformers Usage

Install Transformers

Install Transformers 
pip install -U transformers torch

Load the model and run inference

Load the model and run inference 
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained('mghan3624/bart_qg_finetune_squad')
tokenizer = AutoTokenizer.from_pretrained('mghan3624/bart_qg_finetune_squad')

Full Documentation

来源: HuggingFace

---
license: apache-2.0
datasets:

  • rajpurkar/squad

language:
  • en

metrics:
  • bleu

base_model:
  • facebook/bart-base

pipeline_tag: document-question-answering
---

View official source
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