Ma7ee7/Meet7.1_0.6b
TEXT GENERATIONPricing:Input $0.04 / Cached $0.008 / Output $0.08Concurrent Unit Cost:1Model Size:0.8BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Mar 27, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Warm
Ma7ee7/Meet7.1_0.6b is a 0.8 billion parameter Qwen3 model developed by Ma7ee7, fine-tuned from Ma7ee7/Meet7_0.6b_Exp. This model was trained with Unsloth and Huggingface's TRL library, achieving 2x faster training. It features a 32768 token context length and is optimized for efficient fine-tuning workflows.
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Ma7ee7/Meet7.1_0.6b Model Summary
Ma7ee7/Meet7.1_0.6b is a 0.8 billion parameter Qwen3 model, developed by Ma7ee7. It is a fine-tuned iteration, building upon the base of Ma7ee7/Meet7_0.6b_Exp. This model distinguishes itself through its training methodology, leveraging Unsloth and Huggingface's TRL library, which enabled a 2x acceleration in the training process.
Key Characteristics
- Architecture: Qwen3 base model.
- Parameter Count: 0.8 billion parameters.
- Context Length: Supports a substantial 32768 token context window.
- Training Efficiency: Achieved 2x faster training using Unsloth and Huggingface's TRL library, indicating an optimization for rapid iteration and development.
- License: Released under the Apache-2.0 license, promoting open and flexible use.
Intended Use Cases
This model is particularly well-suited for developers and researchers looking for:
- Efficient Fine-tuning: Its optimized training process makes it a strong candidate for further fine-tuning on specific downstream tasks where rapid experimentation is crucial.
- Applications requiring a moderate parameter count: The 0.8B size offers a balance between performance and computational resource requirements.
- Projects benefiting from a large context window: The 32768 token context length allows for processing and generating longer sequences of text.