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IntelligentEstate/Mjollnir-3B-iQ5-K_S-GGUF
Mjollnir-3B-iQ5-K_S-GGUF is a machine learning model from IntelligentEstate. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as gpl.
<div align="center" <h1 Project-VEGA: Q-Mjollnir-3B-iQ5 </h1 </div
Downloads · 30 days
41
13% of all-time downloads
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.gguf2.2 GB · 100%
From the Hugging Face model README
[!TIP] This Model in not censored and limit broken, Tested on a closed system please use and transfer with caution. This model is more function based We are working on the Llama version for Gaming and effective on device assistance in the real world
A low rescource frontier GitC(Guy in the Chair) model with multi-in-turn-function calling.(This model is a GPT4.5 style model) From Project VEGA. This little model is meant to be the perfect low key tactical assistant. Batman Has Alfred, Iron man has Jarvis and you, you beautiful son of a bitch well you have Mjollnir. Even if it's just for a walkthrough of doom or to take down the cabal of local bullies This little model has your back. Should work on Android and Apple, PC or Mac.

This is an application of a small Effective non-reasoning tool use model with Multiple in turn Tool User for all devices. This little baby doesn't just have reasoning and tool use but multiple tool use and exceptional insight for its little size. It brings an awesome amount of functionality and usefulness to edge setups and is specifically built as a functional mobile assistant. For its size it leads the frontier.
This model beats OpenAI models in Function calling in an overall score on Berkeley Function-Calling Leaderboard (BFCL-v3). It was converted using a custom importance matrix specialized for tool use in the real world. Vector smoothing and S-AGI gives this model better overall responce and assistant capabilities than any other in it's class.
The Mjollnir model, fine-tuned from the Hammer 2.1 and Qwen 2.5 coder series, inherit Many advantages and are enhanced as follows:
Further enhanced through a task specific Importance matrix to ensure real world application and relevance where applicable.
The evaluation results of Base Hammer 2.1 3B model on the Berkeley Function-Calling Leaderboard (BFCL-v3) are presented in the following table:

Built from Hammer's 2.1 Model. It showcases highly stable performance over all, suggesting the robustness of Hammer 2.1 series. In contrast, The others in the frontier show only specialized usefulness and overfitting for poor levels of effectiveness in the field. While this runs on 1 cheap samsung some of the models it competes with and beats would require 100 of the same system to run and there are no people who can compete for the tasks in the field.