mindfossil/telecom-intelligence-model-v5-merged
TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:7.6BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jul 28, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The mindfossil/telecom-intelligence-model-v5-merged is a 7.6 billion parameter Qwen2-based causal language model developed by mindfossil. This model was finetuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is specifically designed for applications requiring intelligence within the telecommunications domain, leveraging its Qwen2 architecture and efficient training methodology.
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Overview
The mindfossil/telecom-intelligence-model-v5-merged is a 7.6 billion parameter language model developed by mindfossil. It is built upon the Qwen2 architecture, specifically finetuned from unsloth/qwen2.5-7b-instruct-unsloth-bnb-4bit.
Key Characteristics
- Efficient Training: This model was finetuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process compared to standard methods.
- Domain-Specific Focus: While the base model is general-purpose, the finetuning by mindfossil suggests an optimization for tasks related to telecommunications intelligence.
Potential Use Cases
- Telecom Analytics: Analyzing and generating insights from telecommunications data.
- Network Management: Assisting with intelligent operations and problem-solving in network environments.
- Customer Support Automation: Developing advanced chatbots or virtual assistants for telecom-specific queries.