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speech_captioner_llama-3.1_lora_model
mesut/speech_captioner_llama-3.1_lora_model
speech_captioner_llama-3.1_lora_model is a machine learning model from mesut. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
The unsloth/meta-llama-3.1-8b-bnb-4bit model is fine tuned by 30.000 mp speeches and captions from USA Congress, Senate and House. The system promt is below
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Updated Oct 31, 2024
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At a glance
- Library
- transformers
- License
- apache-2.0
- Access
- Public
- Created
- Oct 31, 2024
- Updated
- Oct 31, 2024
- SHA
- 77406e5b
Base models
Model card
From the Hugging Face model README
Uploaded model
The unsloth/meta-llama-3.1-8b-bnb-4bit model is fine tuned by 30.000 mp speeches and captions from USA Congress, Senate and House. The system promt is below
system_prompt = """You are an expert captioning assistant specializing in converting a speech transcript into clear, accurate, and viewer-friendly captions.
Instruction:
Caption the speech: {}
Input:
{}
Response:
Caption of the speech: {}"""
The data set is curated using
Judd, Nicholas, Dan Drinkard, Jeremy Carbaugh, and Lindsay Young. congressional-record: A parser for the Congressional Record. Chicago, IL: 2017. https://github.com/unitedstates/congressional-record
Text is preprocessed by removing President names, Vice President names, party names, and some cliche phrases such as "I reserve the balance of my time","I yield the floor" etc.
- Developed by: mesut
- License: apache-2.0
- Finetuned from model : unsloth/meta-llama-3.1-8b-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
- Library
- transformers
- License
- apache-2.0
- Languages
- en
- Created
- Oct 31, 2024
- Updated
- Oct 31, 2024