vinoth322006/vibethinker-toolcall-3b-merged
TEXT GENERATIONPricing:Input $0.32 / Cached $0.064 / Output $1.6Concurrent Unit Cost:1Model Size:3.1BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jul 18, 2026License:apache-2.0Architecture:Transformer0.0K Open Weights Featherless Exclusive Cold
vinoth322006/vibethinker-toolcall-3b-merged is a 3.1 billion parameter Qwen2 model, finetuned by vinoth322006 from WeiboAI/VibeThinker-3B. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is designed for tool-calling applications, leveraging its Qwen2 architecture for efficient function execution.
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Model Overview
vinoth322006/vibethinker-toolcall-3b-merged is a 3.1 billion parameter Qwen2 model, finetuned by vinoth322006. It is based on the WeiboAI/VibeThinker-3B model and was developed with a focus on efficient training.
Key Characteristics
- Architecture: Qwen2 base model, indicating strong general language understanding capabilities.
- Parameter Count: 3.1 billion parameters, offering a balance between performance and computational efficiency.
- Training Efficiency: Finetuned using Unsloth and Huggingface's TRL library, resulting in 2x faster training compared to standard methods.
- License: Distributed under the Apache-2.0 license.
Potential Use Cases
This model is particularly suited for applications requiring:
- Tool Calling: Its finetuned nature suggests optimization for scenarios where the model needs to interact with external tools or APIs.
- Efficient Deployment: The smaller parameter count (3.1B) makes it suitable for environments with limited computational resources.
- Research and Development: Provides a base for further experimentation and finetuning on specific tasks, especially those benefiting from faster training cycles.