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---
base_model: unsloth/llama-3-8b-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- gguf
datasets:
- Ken4070TiS/qubit_arXiv
---
This model was made by the following step:
1. Use a web crawler to collect the papers by using arXiv API.
2. The searching keyword is "qubit AND (IBM OR IQM OR Rigetti)", the time range is 2018 - 2024.
3. The data was corrected in the JSON with column' Title, Abstract, Authors, arXiv_id, Date, Author_company.
4. Feed the JSON files to llama-3-8b-bnb-4bit and fine-tune the model by using unsloth on google colab, the GPU is A100
5. That's it! :)
# Uploaded model
- **Developed by:** Ken4070TiS
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth) |