vallepubalaji53/orderbot-v4-model
TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:8kPublished:Apr 15, 2026Architecture:Transformer Warm
The vallepubalaji53/orderbot-v4-model is an 8 billion parameter language model, fine-tuned using Unsloth for enhanced training speed. It features an 8192 token context length and is provided in GGUF format for efficient deployment. This model is optimized for specific conversational or task-oriented applications, leveraging its fine-tuning for improved performance in its intended domain.
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Overview
The vallepubalaji53/orderbot-v4-model is an 8 billion parameter language model, specifically fine-tuned and converted to the GGUF format. This model leverages Unsloth for its training process, which significantly accelerates fine-tuning, reportedly achieving 2x faster training times.
Key Capabilities
- Efficient Deployment: Provided in GGUF format, making it suitable for local inference and various hardware configurations.
- Accelerated Training: Benefits from Unsloth's optimizations, allowing for quicker fine-tuning cycles.
- Standard Interface: Compatible with
llama-clifor text-only applications andllama-mtmd-clifor multimodal use cases, utilizing the--jinjaflag for prompt templating.
Good For
- Resource-Constrained Environments: The GGUF format is ideal for deployment on consumer hardware.
- Rapid Prototyping: Developers can quickly integrate and test this model due to its efficient format and standard CLI usage.
- Specific Conversational Tasks: While the exact fine-tuning domain isn't detailed, its name suggests optimization for order-related or bot interactions.