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Update Aura-1-Coding: distilled QLoRA adapters from Qwen2.5-3B into GPT-2 XL

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README.md CHANGED
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  ---
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- license: llama3.1
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- base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
 
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  tags:
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- - code
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- - text-generation
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- - distilled
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  ---
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- # Aura-1-Coding (Standalone 4-Bit Variant)
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- Aura-1-Coding is an ultra-fast, standalone code generation model optimized using localized high-density distillation loops. Built on top of the `Meta-Llama-3.1-8B-Instruct` architecture, it features a protected, internal chain-of-thought system designed to execute complex operations without raw reasoning exposure, preventing multi-level distillation attacks and consumer dilution.
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- ---
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- ## ⚡ Performance Footprint & Specifications
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- The primary execution architecture operates under the following hardware parameters:
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- | Metric / Component | Configuration Specification |
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- | :--- | :--- |
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- | **Base Architecture** | Meta-Llama-3.1-8B-Instruct |
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- | **Quantization Format** | 4-Bit NormalFloat (`NF4`) with Double Quantization |
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- | **Compute Data Type** | `Float16` Execution Gates |
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- | **Optimizer Blueprint** | 8-Bit Paged Memory Managed |
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- | **Target Alignment** | High-Density Multi-File Coding Stack |
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- | **VRAM Operational Footprint** | ~5.5 GiB (Ideal for consumer-grade GPU pipelines) |
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- ## 📁 Repository Structure
 
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- The primary model assets are isolated inside the main distribution branch:
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- ```text
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- waveforce-ai/Aura-1-Coding/
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- └── aura-1-coding-model-file/
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- └── model.safetensors <- [5.70 GB Standalone Weights Binary]
 
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+ base_model: gpt2-xl
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+ library_name: peft
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+ pipeline_tag: text-generation
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  tags:
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+ - base_model:adapter:gpt2-xl
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+ - lora
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+ - transformers
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  ---
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+ # Model Card for Model ID
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+ <!-- Provide a quick summary of what the model is/does. -->
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+ ## Model Details
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+ ### Model Description
 
 
 
 
 
 
 
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+ <!-- Provide a longer summary of what this model is. -->
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+
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+
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+
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+ - **Developed by:** [More Information Needed]
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+ - **Funded by [optional]:** [More Information Needed]
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+ - **Shared by [optional]:** [More Information Needed]
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+ - **Model type:** [More Information Needed]
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+ - **Language(s) (NLP):** [More Information Needed]
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+ - **License:** [More Information Needed]
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+ - **Finetuned from model [optional]:** [More Information Needed]
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+
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+ ### Model Sources [optional]
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+
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+ <!-- Provide the basic links for the model. -->
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+
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+ - **Repository:** [More Information Needed]
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+ - **Paper [optional]:** [More Information Needed]
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+ - **Demo [optional]:** [More Information Needed]
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+
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+ ## Uses
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+
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+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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+
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+ ### Direct Use
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+
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+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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+
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+ [More Information Needed]
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+
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+ ### Downstream Use [optional]
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+
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+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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+
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+ [More Information Needed]
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+
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+ ### Out-of-Scope Use
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+
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+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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+
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+ [More Information Needed]
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+
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+ ## Bias, Risks, and Limitations
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+
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+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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+
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+ [More Information Needed]
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+
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+ ### Recommendations
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+
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+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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+
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+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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+
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+ ## How to Get Started with the Model
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+
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+ Use the code below to get started with the model.
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+
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+ [More Information Needed]
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+
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+ ## Training Details
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+
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+ ### Training Data
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+
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+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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+
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+ [More Information Needed]
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+
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+ ### Training Procedure
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+
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+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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+
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+ #### Preprocessing [optional]
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+
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+ [More Information Needed]
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+
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+
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+ #### Training Hyperparameters
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+
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+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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+
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+ #### Speeds, Sizes, Times [optional]
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+
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+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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+ [More Information Needed]
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+
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+ ## Evaluation
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+
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+ <!-- This section describes the evaluation protocols and provides the results. -->
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+
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+ ### Testing Data, Factors & Metrics
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+
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+ #### Testing Data
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+
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+ <!-- This should link to a Dataset Card if possible. -->
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+
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+ [More Information Needed]
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+
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+ #### Factors
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+
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+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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+
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+ [More Information Needed]
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+
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+ #### Metrics
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+
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+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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+ [More Information Needed]
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+ ### Results
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+ [More Information Needed]
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+
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+ #### Summary
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+ ## Model Examination [optional]
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+
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+ <!-- Relevant interpretability work for the model goes here -->
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+ [More Information Needed]
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+ ## Environmental Impact
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+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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+
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+ - **Hardware Type:** [More Information Needed]
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+ - **Hours used:** [More Information Needed]
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+ - **Cloud Provider:** [More Information Needed]
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+ - **Compute Region:** [More Information Needed]
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+ - **Carbon Emitted:** [More Information Needed]
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+
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+ ## Technical Specifications [optional]
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+
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+ ### Model Architecture and Objective
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+
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+ [More Information Needed]
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+
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+ ### Compute Infrastructure
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+
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+ [More Information Needed]
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+ #### Hardware
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+ [More Information Needed]
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+
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+ #### Software
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+ [More Information Needed]
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+
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+ ## Citation [optional]
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+
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+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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+ **BibTeX:**
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+ [More Information Needed]
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+ **APA:**
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+ [More Information Needed]
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+
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+ ## Glossary [optional]
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+
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+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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+ [More Information Needed]
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+ ## More Information [optional]
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+ [More Information Needed]
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+ ## Model Card Authors [optional]
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+ [More Information Needed]
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+ ## Model Card Contact
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+ [More Information Needed]
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+ ### Framework versions
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+ - PEFT 0.21.2
 
 
 
 
adapter_config.json ADDED
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+ "loftq_config": {},
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+ "lora_alpha": 32,
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+ "lora_bias": false,
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+ "lora_dropout": 0.05,
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+ "lora_ga_config": null,
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+ "megatron_core": "megatron.core",
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+ "monteclora_config": null,
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+ "peft_type": "LORA",
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+ "peft_version": "0.21.2",
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+ "qalora_group_size": 16,
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+ "r": 16,
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+ "rank_pattern": {},
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+ "revision": null,
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+ "target_modules": [
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+ "c_attn",
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+ "c_proj"
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+ ],
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+ "target_parameters": null,
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+ "task_type": "CAUSAL_LM",
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+ "trainable_token_indices": null,
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+ "use_bdlora": null,
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+ "use_dora": false,
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+ "use_qalora": false,
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+ "use_rslora": false,
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+ "velora_config": null
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+ }
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