Ramikan-BR/Qwen2-0.5B-v30
TEXT GENERATIONPricing:Input $0.04 / Cached $0.008 / Output $0.08Concurrent Unit Cost:1Model Size:0.5BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Aug 11, 2024License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Warm
Ramikan-BR/Qwen2-0.5B-v30 is a 0.5 billion parameter Qwen2 model developed by Ramikan-BR, fine-tuned from unsloth/qwen2-0.5b-bnb-4bit. This model was trained 2x faster using Unsloth and Huggingface's TRL library, offering a 32768 token context length. It is optimized for instruction-following tasks, demonstrating capabilities in sequence continuation and basic code generation.
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Ramikan-BR/Qwen2-0.5B-v30 Overview
This model is a 0.5 billion parameter variant of the Qwen2 architecture, developed by Ramikan-BR. It was fine-tuned from the unsloth/qwen2-0.5b-bnb-4bit model, leveraging Unsloth and Huggingface's TRL library for accelerated training, achieving 2x faster training speeds. The model supports a substantial context length of 32768 tokens.
Key Capabilities
- Instruction Following: Demonstrates proficiency in responding to direct instructions, such as continuing numerical sequences (e.g., Fibonacci).
- Basic Code Generation: Capable of generating simple code snippets based on natural language prompts, as shown by its ability to produce Python code for a game.
- Efficient Training: Benefits from Unsloth's optimization, making it a potentially efficient choice for resource-constrained environments or rapid prototyping.
Good For
- Instruction-based tasks: Ideal for applications requiring the model to follow specific commands or complete patterns.
- Lightweight code assistance: Suitable for generating boilerplate code or simple programming logic.
- Experimentation: Its smaller size and efficient training make it a good candidate for quick iterations and testing in development workflows.