sandeeparmada/mistalai_finetuned

TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:7BQuant:FP8Context Size:4kTool Calling:SupportedPublished:Aug 16, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The sandeeparmada/mistalai_finetuned model is a 7 billion parameter instruction-tuned causal language model, finetuned from unsloth/mistral-7b-instruct-v0.3-bnb-4bit. Developed by sandeeparmada, this model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is designed for general instruction-following tasks, leveraging the Mistral architecture's efficiency.

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Model Overview

The sandeeparmada/mistalai_finetuned model is a 7 billion parameter instruction-tuned language model. It was developed by sandeeparmada and is based on the unsloth/mistral-7b-instruct-v0.3-bnb-4bit architecture, leveraging the Mistral family's efficient design.

Key Characteristics

  • Base Model: Finetuned from unsloth/mistral-7b-instruct-v0.3-bnb-4bit.
  • Training Efficiency: The model was trained with Unsloth and Huggingface's TRL library, which enabled a 2x faster training process compared to standard methods.
  • Parameter Count: Features 7 billion parameters, offering a balance between performance and computational requirements.
  • License: Distributed under the Apache-2.0 license, allowing for broad use and modification.

Potential Use Cases

This model is suitable for a variety of instruction-following tasks, benefiting from its Mistral base and optimized finetuning. Its efficient training process suggests it could be a good candidate for applications requiring a capable yet resource-conscious language model.