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62 changes: 62 additions & 0 deletions gallery/index.yaml
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@@ -1,4 +1,66 @@
---
- name: "qwopus-glm-18b-merged"
url: "github:mudler/LocalAI/gallery/virtual.yaml@master"
urls:
- https://huggingface.co/Jackrong/Qwopus-GLM-18B-Merged-GGUF
description: |
# 🪐 Qwen3.5-9B-GLM5.1-Distill-v1

## 📌 Model Overview

**Model Name:** `Jackrong/Qwen3.5-9B-GLM5.1-Distill-v1`
**Base Model:** Qwen3.5-9B
**Training Type:** Supervised Fine-Tuning (SFT, Distillation)
**Parameter Scale:** 9B
**Training Framework:** Unsloth

This model is a distilled variant of **Qwen3.5-9B**, trained on high-quality reasoning data derived from **GLM-5.1**.

The primary goals are to:

- Improve **structured reasoning ability**
- Enhance **instruction-following consistency**
- Activate **latent knowledge via better reasoning structure**

## 📊 Training Data

### Main Dataset

- `Jackrong/GLM-5.1-Reasoning-1M-Cleaned`
- Cleaned from the original `Kassadin88/GLM-5.1-1000000x` dataset.
- Generated from a **GLM-5.1 teacher model**
- Approximately **700x** the scale of `Qwen3.5-reasoning-700x`
- Training used a **filtered subset**, not the full source dataset.

### Auxiliary Dataset

- `Jackrong/Qwen3.5-reasoning-700x`

...
license: "apache-2.0"
tags:
- llm
- gguf
- reasoning
icon: https://cdn-uploads.huggingface.co/production/uploads/66309bd090589b7c65950665/BnSg_x99v9bG9T5-8sKa1.png
overrides:
backend: llama-cpp
function:
automatic_tool_parsing_fallback: true
grammar:
disable: true
known_usecases:
- chat
options:
- use_jinja:true
parameters:
model: llama-cpp/models/Qwopus-GLM-18B-Merged-GGUF/Qwopus-GLM-18B-Healed-Q4_K_M.gguf
template:
use_tokenizer_template: true
files:
- filename: llama-cpp/models/Qwopus-GLM-18B-Merged-GGUF/Qwopus-GLM-18B-Healed-Q4_K_M.gguf
sha256: 13bd039f95c9ea46ef1d75905faa7be6ca4e47a5af9d4cf62e298a738a5b195f
uri: https://huggingface.co/Jackrong/Qwopus-GLM-18B-Merged-GGUF/resolve/main/Qwopus-GLM-18B-Healed-Q4_K_M.gguf
- name: "qwen3.6-35b-a3b-apex"
url: "github:mudler/LocalAI/gallery/virtual.yaml@master"
urls:
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- "offload_to_cpu:false"
- "offload_dit_to_cpu:false"
- "init_lm:true"
- "lm_model_path:acestep-5Hz-lm-0.6B" # or acestep-5Hz-lm-4B

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- "lm_backend:pt"
- "temperature:0.85"
- "top_p:0.9"
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known_usecases:
- tts
tts:
voice: Aiden # Available speakers: Vivian, Serena, Uncle_Fu, Dylan, Eric, Ryan, Aiden, Ono_Anna, Sohee

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parameters:
model: Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice
- !!merge <<: *qwen-tts
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known_usecases:
- tts
tts:
voice: Aiden # Available speakers: Vivian, Serena, Uncle_Fu, Dylan, Eric, Ryan, Aiden, Ono_Anna, Sohee

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parameters:
model: Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice
- &fish-speech
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- gemma3
- gemma-3
overrides:
#mmproj: gemma-3-27b-it-mmproj-f16.gguf

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parameters:
model: gemma-3-27b-it-Q4_K_M.gguf
files:
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description: |
google/gemma-3-12b-it is an open-source, state-of-the-art, lightweight, multimodal model built from the same research and technology used to create the Gemini models. It is capable of handling text and image input and generating text output. It has a large context window of 128K tokens and supports over 140 languages. The 12B variant has been fine-tuned using the instruction-tuning approach. Gemma 3 models are suitable for a variety of text generation and image understanding tasks, including question answering, summarization, and reasoning. Their relatively small size makes them deployable in environments with limited resources such as laptops, desktops, or your own cloud infrastructure.
overrides:
#mmproj: gemma-3-12b-it-mmproj-f16.gguf

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parameters:
model: gemma-3-12b-it-Q4_K_M.gguf
files:
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description: |
Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models. Gemma 3 models are multimodal, handling text and image input and generating text output, with open weights for both pre-trained variants and instruction-tuned variants. Gemma 3 has a large, 128K context window, multilingual support in over 140 languages, and is available in more sizes than previous versions. Gemma 3 models are well-suited for a variety of text generation and image understanding tasks, including question answering, summarization, and reasoning. Their relatively small size makes it possible to deploy them in environments with limited resources such as laptops, desktops or your own cloud infrastructure, democratizing access to state of the art AI models and helping foster innovation for everyone. Gemma-3-4b-it is a 4 billion parameter model.
overrides:
#mmproj: gemma-3-4b-it-mmproj-f16.gguf

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parameters:
model: gemma-3-4b-it-Q4_K_M.gguf
files:
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