dkhush06/Qwen2.5-7B-Browser-Agent-Merged
TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:7.6BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 2, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The dkhush06/Qwen2.5-7B-Browser-Agent-Merged is a 7.6 billion parameter language model, finetuned by dkhush06 from unsloth/Qwen2.5-7B-Instruct-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, enabling faster training times. It is designed for general language understanding and generation tasks, leveraging the Qwen2.5 architecture.
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Model Overview
The dkhush06/Qwen2.5-7B-Browser-Agent-Merged is a 7.6 billion parameter language model, developed by dkhush06. It is a finetuned version of the unsloth/Qwen2.5-7B-Instruct-bnb-4bit model, leveraging the Qwen2.5 architecture.
Key Characteristics
- Efficient Training: This model was trained significantly faster (2x) using the Unsloth library in conjunction with Huggingface's TRL library. Unsloth is known for optimizing the training process for large language models.
- Base Model: It builds upon the Qwen2.5-7B-Instruct foundation, suggesting strong capabilities in instruction following and general conversational tasks.
- License: The model is released under the Apache-2.0 license, allowing for broad use and distribution.
Potential Use Cases
Given its instruction-tuned base and efficient training, this model is suitable for:
- General-purpose text generation and understanding.
- Chatbot applications requiring instruction adherence.
- Further fine-tuning for specific domain tasks where the Qwen2.5 architecture is beneficial.