Martico2432/mcollm1-2b

MCOLLM-2b

A simple 2b model, fine-tuned version of the Gemma 2b model, optimized for step by step thinking

Model Details

Model Description

• Developed by: Martico2432
• Model type: Causal Language Model (transformer)
• Language(s) (NLP): English
• License: Apache-2.0
• Finetuned from model: Gemma-2B

Model Sources

• Repository: (https://huggingface.co/google/gemma-2b)

Uses

Direct Use

• Chatbots and conversational AI applications
• Text generation for creative or educational purposes
• Experimentation with LoRA fine-tuning on small datasets

Downstream Use

• Can be further fine-tuned for any specific tasks

Out-of-Scope Use

• Not designed for high-stakes decision making (legal, medical, safety-critical)
• May generate biased, offensive, or factually incorrect text
• Limited generalization due to small fine-tuning dataset

Bias, Risks, and Limitations

• Fine-tuned on a very small dataset (1000 examples) → risk of overfitting or narrow outputs
• Model may inherit biases from base Gemma‑2B
• Outputs should be critically evaluated before deployment

Recommendations

• Monitor outputs for unsafe or biased content
• Use in low-stakes research or prototyping environments

How to Get Started with the Model

You can get started by using the example in the files

Training Details

Training Data

• 1000 examples of thinking
• Gemma 2b tokenizer

Training Procedure

• Fine-tuning via LoRA on top of Gemma-2B base
• 3 epochs, small learning rate

Training Hyperparameters

• Training regime: fp16 mixed precision

Model Examination [optional]

[More Information Needed]

Environmental Impact

• Hardware Type: T4
• Hours used: 0.5
• Cloud Provider: Google Cloud
• Compute Region: EU
• Carbon Emitted: 0.01kg