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35 changes: 35 additions & 0 deletions gallery/index.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -3822,6 +3822,41 @@
- filename: boomerang-qwen3-4.9B.Q4_K_M.gguf
sha256: 11e6c068351d104dee31dd63550e5e2fc9be70467c1cfc07a6f84030cb701537
uri: huggingface://mradermacher/boomerang-qwen3-4.9B-GGUF/boomerang-qwen3-4.9B.Q4_K_M.gguf
- !!merge <<: *qwen3
name: "qwen3-coder-30b-a3b-instruct"
icon: https://cdn-avatars.huggingface.co/v1/production/uploads/620760a26e3b7210c2ff1943/-s1gyJfvbE1RgO5iBeNOi.png
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a model config url is missing here. Take a look at #8088 for an example of a model import

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Whoops! Let me fix it quickly.

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Added url: "github:mudler/LocalAI/gallery/qwen3.yaml@master".

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I thought this carries over from the main Qwen 3 entry, since it is a merged entry. My bad.

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@mudler mudler Jan 17, 2026

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ouch. you are actually right. I have been misleaded when I saw the description - I thought you were adding the model without the anchor. You are right, if there is an anchor everything is carried over, and other entries are overridden, sorry!

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Should I undo it then?

url: "github:mudler/LocalAI/gallery/qwen3.yaml@master"
urls:
- https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct
- https://huggingface.co/unsloth/Qwen3-Coder-30B-A3B-Instruct-GGUF
description: |
Qwen3-Coder is available in multiple sizes. Today, we're excited to introduce Qwen3-Coder-30B-A3B-Instruct. This streamlined model maintains impressive performance and efficiency, featuring the following key enhancements:

- Significant Performance among open models on Agentic Coding, Agentic Browser-Use, and other foundational coding tasks.
- Long-context Capabilities with native support for 256K tokens, extendable up to 1M tokens using Yarn, optimized for repository-scale understanding.
- Agentic Coding supporting for most platform such as Qwen Code, CLINE, featuring a specially designed function call format.


Model Overview:
Qwen3-Coder-30B-A3B-Instruct has the following features:

- Type: Causal Language Models
- Training Stage: Pretraining & Post-training
- Number of Parameters: 30.5B in total and 3.3B activated
- Number of Layers: 48
- Number of Attention Heads (GQA): 32 for Q and 4 for KV
- Number of Experts: 128
- Number of Activated Experts: 8
- Context Length: 262,144 natively.

NOTE: This model supports only non-thinking mode and does not generate <think></think> blocks in its output. Meanwhile, specifying enable_thinking=False is no longer required.
overrides:
parameters:
model: Qwen3-Coder-30B-A3B-Instruct-Q4_K_M.gguf
files:
- filename: Qwen3-Coder-30B-A3B-Instruct-Q4_K_M.gguf
sha256: fadc3e5f8d42bf7e894a785b05082e47daee4df26680389817e2093056f088ad
uri: huggingface://unsloth/Qwen3-Coder-30B-A3B-Instruct-GGUF/Qwen3-Coder-30B-A3B-Instruct-Q4_K_M.gguf
- &gemma3
url: "github:mudler/LocalAI/gallery/gemma.yaml@master"
name: "gemma-3-27b-it"
Expand All @@ -3841,7 +3876,7 @@
- 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:
Expand All @@ -3859,7 +3894,7 @@
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:
Expand All @@ -3877,7 +3912,7 @@
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:
Expand Down Expand Up @@ -7095,7 +7130,7 @@
sha256: 2756551de7d8ff7093c2c5eec1cd00f1868bc128433af53f5a8d434091d4eb5a
uri: huggingface://Triangle104/Nano_Imp_1B-Q8_0-GGUF/nano_imp_1b-q8_0.gguf
- &smollm
url: "github:mudler/LocalAI/gallery/chatml.yaml@master" ## SmolLM

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name: "smollm-1.7b-instruct"
icon: https://huggingface.co/datasets/HuggingFaceTB/images/resolve/main/banner_smol.png
tags:
Expand Down Expand Up @@ -7139,7 +7174,7 @@
sha256: decd2598bc2c8ed08c19adc3c8fdd461ee19ed5708679d1c54ef54a5a30d4f33
uri: huggingface://HuggingFaceTB/SmolLM2-1.7B-Instruct-GGUF/smollm2-1.7b-instruct-q4_k_m.gguf
- &llama31
url: "github:mudler/LocalAI/gallery/llama3.1-instruct.yaml@master" ## LLama3.1

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icon: https://avatars.githubusercontent.com/u/153379578
name: "meta-llama-3.1-8b-instruct"
license: llama3.1
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