srcho37/day1-train-model
TEXT GENERATIONConcurrency Cost:1Model Size:0.5BQuant:BF16Ctx Length:32kPublished:Mar 25, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
The srcho37/day1-train-model is a 0.5 billion parameter Qwen2.5-based instruction-tuned causal language model developed by srcho37. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general language tasks, leveraging its efficient training methodology.
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Model Overview
The srcho37/day1-train-model is a 0.5 billion parameter instruction-tuned language model based on the Qwen2.5 architecture. Developed by srcho37, this model was fine-tuned from unsloth/Qwen2.5-0.5B-Instruct-unsloth-bnb-4bit.
Key Characteristics
- Efficient Training: This model was trained 2x faster by utilizing Unsloth and Huggingface's TRL library, highlighting an optimized fine-tuning process.
- Architecture: Built upon the Qwen2.5 foundation, it benefits from the advancements in that model family.
- Parameter Count: With 0.5 billion parameters, it offers a compact size suitable for various applications.
- Context Length: Supports a context length of 32768 tokens.
Good For
- General Language Tasks: Suitable for a range of instruction-following applications due to its instruction-tuned nature.
- Resource-Efficient Deployment: Its smaller parameter count makes it potentially suitable for environments with limited computational resources.
- Exploring Efficient Fine-tuning: Demonstrates the practical application of Unsloth for accelerated model training.