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Model: Likithp/v10_gemma3_1B_fixed_s42
Source: Original Platform

.gitattributes

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README.md

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+---
+library_name: transformers
+tags: []
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+
+- **Developed by:** [More Information Needed]
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+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
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+## Uses
+
+<!-- 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 when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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+### Out-of-Scope Use
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+## Bias, Risks, and Limitations
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+
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+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
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+## Training Details
+
+### Training Data
+
+<!-- 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. -->
+
+#### Preprocessing [optional]
+
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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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+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
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+<!-- This should link to a Dataset Card if possible. -->
+
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+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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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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+
+### Results
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+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
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+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+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).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
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+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
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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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+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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config.json

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+}

epoch_1/config.json

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epoch_1/epoch_meta.json

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epoch_1/generation_config.json

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epoch_1/tokenizer_config.json

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epoch_2/config.json

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epoch_2/tokenizer_config.json

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