casareborgia/my-vrain-new1

TEXT GENERATIONPricing:Input $0.32 / Cached $0.064 / Output $1.6Concurrent Unit Cost:1Model Size:2.6BQuant:BF16Context Size:8kPublished:Jul 26, 2026Architecture:Transformer Featherless Exclusive Cold

my-vrain-new1 is a 2.6 billion parameter language model developed by casareborgia, provided in GGUF format. This model was fine-tuned using Unsloth, enabling faster training and efficient deployment. It is designed for general text generation tasks, with specific instructions for use with llama-cli and Ollama. The model has a context length of 8192 tokens and is optimized for compatibility with GGUF-based inference engines.

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Model Overview

my-vrain-new1 is a 2.6 billion parameter language model developed by casareborgia, distributed in the GGUF format. This model was fine-tuned leveraging the Unsloth library, which facilitated a 2x faster training process. It is specifically packaged for efficient deployment and inference on local hardware.

Key Features and Usage

  • GGUF Format: The model is provided as gemma-2-2b-it.Q4_K_M.gguf, ensuring broad compatibility with various inference engines.
  • Unsloth Optimization: Benefits from Unsloth's optimizations for faster training and potentially improved inference performance.
  • CLI Compatibility: Ready for use with llama-cli for text-only applications and llama-mtmd-cli for multimodal scenarios, both supporting Jinja templating.
  • Ollama Integration: Includes a dedicated Modelfile for straightforward deployment and management within the Ollama ecosystem.
  • BOS Token Adjustment: The model's Beginning-of-Sentence (BOS) token behavior has been specifically adjusted to ensure optimal compatibility with the GGUF specification.

Ideal Use Cases

  • Local Inference: Suited for developers and users looking to run a capable language model locally with efficient resource utilization.
  • Rapid Prototyping: The Unsloth-optimized training makes it a good candidate for projects requiring quick iteration and deployment.
  • GGUF-centric Workflows: Integrates seamlessly into existing workflows that utilize GGUF models and tools like llama.cpp or Ollama.