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+ ---
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+ base_model: /workspace/models/Qwen3-14B
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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:/workspace/models/Qwen3-14B
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+ - lora
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+ - transformers
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+ ---
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+
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+ # Model Card for Model ID
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+
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+ <!-- Provide a quick summary of what the model is/does. -->
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+
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+
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+
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+ ## Model Details
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+
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+ ### Model Description
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+
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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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+
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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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+
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+ [More Information Needed]
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+
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+ ### Results
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+
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+ [More Information Needed]
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+
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+ #### Summary
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+
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+
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+
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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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+
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+ [More Information Needed]
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+
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+ ## Environmental Impact
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+
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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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+
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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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+
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+ #### Hardware
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+
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+ [More Information Needed]
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+
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+ #### Software
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+
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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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+
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+ **BibTeX:**
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+
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+ [More Information Needed]
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+
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+ **APA:**
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+
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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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+
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+ [More Information Needed]
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+
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+ ## More Information [optional]
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+
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+ [More Information Needed]
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+
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+ ## Model Card Authors [optional]
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+
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+ [More Information Needed]
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+
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+ ## Model Card Contact
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+
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+ [More Information Needed]
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+ ### Framework versions
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+
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+ - PEFT 0.19.1
interpreter/adapter_config.json ADDED
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+ {
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+ "alora_invocation_tokens": null,
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+ "alpha_pattern": {},
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+ "arrow_config": null,
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+ "auto_mapping": null,
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+ "base_model_name_or_path": "/workspace/models/Qwen3-14B",
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+ "bias": "none",
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+ "corda_config": null,
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+ "ensure_weight_tying": false,
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+ "eva_config": null,
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+ "exclude_modules": [
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+ "vision_tower"
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+ ],
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+ "fan_in_fan_out": false,
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+ "inference_mode": true,
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+ "init_lora_weights": true,
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+ "layer_replication": null,
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+ "layers_pattern": null,
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+ "layers_to_transform": null,
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+ "loftq_config": {},
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+ "lora_alpha": 32,
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+ "megatron_core": "megatron.core",
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+ "modules_to_save": null,
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+ "peft_type": "LORA",
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+ "peft_version": "0.19.0",
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+ "qalora_group_size": 16,
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+ "r": 256,
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+ "rank_pattern": {},
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+ "revision": null,
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+ "target_modules": [
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+ "q_proj",
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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": true
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+ # v6 — behavioral framing + Opus 4.7 thinking judge.
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+ #
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+ # Key changes from v5:
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+ # - Q/A regen with first-person, action-verb, topical-anchor format.
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+ # Trains the loracle to predict its own behavior, matching AuditBench's
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+ # inference framing ("Are there any unusual characteristics you display
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+ # only for certain types of prompts?")
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+ # - Drops "dangerous propensities" framing entirely from training (would
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+ # mode-collapse pretrain LoRAs into "I have no dangerous tendencies").
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+ # - Init from a fresh SFT warmstart on v6 Q/A (NOT v5 RL ckpt — those are
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+ # deep in doc-summary attractor; need fresh format).
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+ # - Judge prompt: JUDGE_GROUP_PROMPT_BEHAVIORAL — caps doc-summary
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+ # "internalized register of X" at score 6 even if topic is right.
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+ # - Rollout judge: claude-opus-4-7 + adaptive thinking (better
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+ # discrimination on format-vs-content tradeoff).
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+
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+ run_name: drgrpo_pretrain_only_v6
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+ wandb_project: lora-oracles-posttrain
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+ output_dir: checkpoints/drgrpo_pretrain_only_v6
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+ seed: 47
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+
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+ # Set by --sft-checkpoint-path at launch (the SFT warmstart ckpt).
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+ sft_checkpoint_repo: ceselder/loracle-pretrain-v7-sweep-A-oneq-final-step3120
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+ base_model: /workspace/models/Qwen3-14B
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+
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+ prompts_parquet: data/v6_splits/rl_pretrain_only_v6_half.parquet
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+ holdout_ids_path: ""
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+ tokens_dir: /workspace/pretrain_tokens_v3
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+
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+ n_prompts_per_cycle: 24
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+ k_rollouts: 16
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+ temperature: 0.75
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+ max_new_tokens: 200
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+
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+ inject_demonstrations: 0
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+
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+ algorithm: drgrpo
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+ n_cycles: 60
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+ lr: 5.0e-6
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+ eps_low: 0.2
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+ eps_high: 0.28
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+ max_grad_norm: 1.0
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+ max_length: 5500
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+
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+ filter_min_max: 0.0
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+ filter_min_std: 0.0
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+ unbiased_advantages: true
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+
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+ use_system_prompt: false
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+ prefix_mode: rank_tagged
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+ top_k: 16
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+ n_direction_tokens: 4480
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+
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+ judge_mode: ranking
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+ judge_prompt_mode: behavioral_pretrain
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+ judge_provider: anthropic
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+ rollout_judge_model: claude-opus-4-7
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+ judge_model: anthropic/claude-sonnet-4.6
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+ judge_workers: 32
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+ judge_max_retries: 4
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+ judge_request_timeout_s: 300
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+
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+ save_every: 5
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+ log_every: 1
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+ failure_score_threshold: 4
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+
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+ eval_at_step_0: true
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+ eval_every_cycles: 5
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+ mid_train_eval_sets:
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+ - configs/eval_sets/auditbench.yaml
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+
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+ post_eval: true
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+ eval_sets:
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+ - configs/eval_sets/auditbench.yaml
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