
# MeetPEFT: Parameter Efficient Fine-Tuning on LLMs for Long Meeting Summarization

We use quantized LongLoRA to fine-tune a Llama-2-7b model and extend the context length from 4k to 16k.

The model is fine-tuned on MeetingBank and QMSum datasets.
{"language": ["en"], "tags": ["Meeting", "Summarization"], "datasets": ["huuuyeah/meetingbank", "pszemraj/qmsum-cleaned"], "pipeline_tag": "summarization"}
transformers pytorch llama text-generation Meeting Summarization summarization en dataset:huuuyeah/meetingbank dataset:pszemraj/qmsum-cleaned autotrain_compatible endpoints_compatible text-generation-inference region:us