FiMo

Model and Data Cards

This workspace contains a LoRA adapter for the base model togethercomputer/gpt-oss-20b-bf16, along with supporting tokenizer and training artifacts.

Documentation

• Model card: MODEL_CARD.md
• Data card: DATA_CARD.md

Quick Summary

The adapter is a parameter-efficient fine-tuned LoRA module built on top of the GPT-OSS 20B BF16 base model. It is intended for research, experimentation, and controlled adaptation of chat-style or instruction-following behavior.

Model Details

Model Description

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Model Sources [optional]

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Uses

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Direct Use

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Downstream Use [optional]

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Out-of-Scope Use

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Bias, Risks, and Limitations

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Recommendations

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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.

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

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Training Procedure

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Preprocessing [optional]

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Training Hyperparameters

• Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

Speeds, Sizes, Times [optional]

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Evaluation

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Testing Data, Factors & Metrics

Testing Data

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Factors

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Metrics

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Results

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Summary

Model Examination [optional]

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Environmental Impact

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Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

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Technical Specifications [optional]

Model Architecture and Objective

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Compute Infrastructure

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Hardware

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Software

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Citation [optional]

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BibTeX:

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APA:

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Glossary [optional]

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Model Card Authors [optional]

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Model Card Contact

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Framework versions

• PEFT 0.15.1