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        vblora_tuning_mlp/0.12.1.dev0/README.md
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            ---
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            library_name: peft
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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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            - **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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            ### Model Sources [optional]
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            <!-- Provide the basic links for the model. -->
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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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            ## Uses
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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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            ### Direct Use
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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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            [More Information Needed]
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            ### Downstream Use [optional]
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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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            [More Information Needed]
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            ### Out-of-Scope Use
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            <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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            [More Information Needed]
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            ## Bias, Risks, and Limitations
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            <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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            [More Information Needed]
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            ### Recommendations
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            <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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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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            ## How to Get Started with the Model
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            Use the code below to get started with the model.
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            [More Information Needed]
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            ## Training Details
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            ### Training Data
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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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            [More Information Needed]
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            ### Training Procedure
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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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            #### Preprocessing [optional]
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            [More Information Needed]
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            #### Training Hyperparameters
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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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            #### Speeds, Sizes, Times [optional]
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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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            ## Evaluation
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            <!-- This section describes the evaluation protocols and provides the results. -->
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            ### Testing Data, Factors & Metrics
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            #### Testing Data
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            <!-- This should link to a Dataset Card if possible. -->
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            [More Information Needed]
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            #### Factors
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            <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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            [More Information Needed]
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            #### Metrics
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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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            #### Summary
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            ## Model Examination [optional]
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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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            - **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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            ## Technical Specifications [optional]
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            ### Model Architecture and Objective
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            [More Information Needed]
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            ### Compute Infrastructure
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            [More Information Needed]
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            #### Hardware
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            [More Information Needed]
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            #### Software
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            [More Information Needed]
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            ## Citation [optional]
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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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            ## Glossary [optional]
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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 0.12.1.dev0
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        vblora_tuning_mlp/0.12.1.dev0/adapter_config.json
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            {
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              "auto_mapping": {
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                "base_model_class": "MLP",
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                "parent_library": "test_regression"
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              },
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              "base_model_name_or_path": null,
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              "bias": "none",
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              "fan_in_fan_out": false,
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              "inference_mode": true,
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              "init_logits_std": 0.1,
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              "init_vector_bank_bound": 0.02,
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              "layers_pattern": null,
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              "layers_to_transform": null,
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              "modules_to_save": null,
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              "num_vectors": 2,
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              "peft_type": "VBLORA",
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              "r": 4,
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              "revision": null,
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              "save_only_topk_weights": false,
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              "target_modules": [
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                "lin0"
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              ],
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              "task_type": null,
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              "topk": 2,
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              "vblora_dropout": 0.0,
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              "vector_length": 1
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            }
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        vblora_tuning_mlp/0.12.1.dev0/adapter_model.safetensors
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            version https://git-lfs.github.com/spec/v1
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            size 1296
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        vblora_tuning_mlp/0.12.1.dev0/output.pt
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            version https://git-lfs.github.com/spec/v1
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            oid sha256:797f85a691240dd906d2cd227d8a343d3a0ad72c633e7ec3bc23f1d2a070b3ca
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            size 1239
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