|
--- |
|
license: other |
|
language: |
|
- en |
|
pipeline_tag: text-generation |
|
inference: false |
|
tags: |
|
- pytorch |
|
- llama |
|
- llama-2 |
|
- qCammel-13 |
|
library_name: transformers |
|
--- |
|
# qCammel-13 |
|
qCammel-13 is a fine-tuned version of Llama-2 13B model, trained on a distilled dataset of 15,000 instructions using QLoRA. This model is optimized for academic medical knowledge and instruction-following capabilities. |
|
|
|
## Model Details |
|
*Note: Use of this model is governed by the Meta license. In order to download the model weights and tokenizer, please visit the [website](https://ai.meta.com/resources/models-and-libraries/llama-downloads/) and accept their License before downloading this model .* |
|
|
|
The fine-tuning process applied to qCammel-13 involves a distilled dataset of 15,000 instructions and is trained with QLoRA, |
|
|
|
|
|
**Variations** The original Llama 2 has parameter sizes of 7B, 13B, and 70B. This is the fine-tuned version of the 13B model. |
|
|
|
**Input** Models input text only. |
|
|
|
**Output** Models generate text only. |
|
|
|
**Model Architecture** qCammel-13 is based on the Llama 2 architecture, an auto-regressive language model that uses a decoder only transformer architecture. |
|
|
|
**License** A custom commercial license is available at: [https://ai.meta.com/resources/models-and-libraries/llama-downloads/](https://ai.meta.com/resources/models-and-libraries/llama-downloads/) |
|
Llama 2 is licensed under the LLAMA 2 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved |
|
|
|
**Research Papers** |
|
- [Clinical Camel: An Open-Source Expert-Level Medical Language Model with Dialogue-Based Knowledge Encoding](https://arxiv.org/abs/2305.12031) |
|
- [QLoRA: Efficient Finetuning of Quantized LLMs](https://arxiv.org/abs/2305.14314) |
|
- [LLaMA: Open and Efficient Foundation Language Models](https://arxiv.org/abs/2302.13971) |
|
|
|
|
|
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) |
|
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_augtoma__qCammel-13) |
|
|
|
| Metric | Value | |
|
|-----------------------|---------------------------| |
|
| Avg. | 48.98 | |
|
| ARC (25-shot) | 60.84 | |
|
| HellaSwag (10-shot) | 83.66 | |
|
| MMLU (5-shot) | 56.73 | |
|
| TruthfulQA (0-shot) | 47.54 | |
|
| Winogrande (5-shot) | 76.16 | |
|
| GSM8K (5-shot) | 11.37 | |
|
| DROP (3-shot) | 6.57 | |
|
|