README.md

---
license: apache-2.0
language:
- en
base_model:
- meta-llama/Llama-3.1-8B-instruct
pipeline_tag: text-generation
tags:
- lora
- adapter
- writing
- CoT
---
# Merged-Llama-Adapters-317-320

A merged LoRA adapter combining four fine-tuned adapters (317-320) for the Llama-3.1-8B language model.

## Model Details

- Base Model: meta-llama/Llama-3.1-8B-instruct
- Adaptation Method: Merged LoRA

## Merger Configuration

### Source Adapters

All source adapters share the following configuration:
- Rank (r): 16
- Alpha: 16
- Target Modules:
  - q_proj (Query projection)
  - k_proj (Key projection)
  - v_proj (Value projection)
  - o_proj (Output projection)
  - up_proj (Upsampling projection)
  - down_proj (Downsampling projection)
  - gate_proj (Gate projection)

### Merger Details

- Merger Method: Linear interpolation
- Merger Weights: Equal weights (0.25) for each adapter
- Combined Rank: 16 (maintained from source adapters)

## Usage

This merged adapter must be used with the base Llama-3.1-8B-instruct model.

## Limitations and Biases

- This merged adapter inherits limitations and biases from:
  - The base Llama-3.1-8B-instruct model
  - More baises from traning data as most of them were fiction work.
- The merging process may result in:
  - Potential loss of specialized capabilities from individual adapters
  - Averaged behavior across different adapter specializations
  - Possible interference between adapter weights

## Merging Process

The adapters were merged using the following approach:
1. Linear interpolation of adapter weights
2. Equal weighting (0.25) applied to each source adapter
3. Preservation of original LoRA rank and architecture

### Method Used

The adapters were merged using PEFT (Parameter-Efficient Fine-Tuning) library's weighted adapter combination feature. The process combines multiple LoRA adapters using linear interpolation with specified weights.


### Key Parameters

- `combination_type="ties"`: Uses the TIES (Task Interference Edge Selection) method for combining adapters
- `density=0.2`: Controls the sparsity of the merged weights


### Notes

- The order of loading adapters may affect the final result
- Equal weights were chosen to maintain balanced influence from each adapter
- The merged adapter maintains the same architecture and rank as the original adapters
- While this adapter merges multiple fine-tunes, each component was developed as part of independent research efforts to explore and language model capabilities as part of R&D process.


## Datasets

- Not yet released, but should be released after evaluation has completed.
- Only 1k pairs example of revision task <input_text> + <style_guide> => <thinking> <-> </revised_text>

### Use Cases

- This merged adapter can be used for a wide range of tasks, including but not limited to:
  - Accessibility
  - Revision & Editing
  - instruction-following use with xml tags
  - Thinking & reasoning with xml tag of <thinking> and </thinking>, if being asked i the instructions.
  

These Models not optimized for code, math, or other specialized tasks that need Perefence Optimization.

## Why SFT Instead of RLHF/DPO?
- RLHF and DPO approaches often lead to vocabulary limitations and overfitting due to their optimization objectives

## License

Licensed under Apache 2.0 License.

This merged adapter is part of independent individual research work. While the code is open-source under the Apache 2.0 license, please note:

- You are free to use, modify, and distribute this adapter following the Apache 2.0 license terms
- This work is provided "as is" without warranties or conditions of any kind
- This is an independent research project and not affiliated with any organization
- Attribution is appreciated but not required
- For full license details, see: https://www.apache.org/licenses/LICENSE-2.0