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chore(model-gallery): ⬆️ update checksum (#9522)
⬆️ Checksum updates in gallery/index.yaml Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
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LocalAI [bot]
@@ -3,40 +3,7 @@
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url: "github:mudler/LocalAI/gallery/virtual.yaml@master"
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urls:
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- https://huggingface.co/KyleHessling1/Qwopus-GLM-18B-Merged-GGUF
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description: |
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# 🪐 Qwen3.5-9B-GLM5.1-Distill-v1
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## 📌 Model Overview
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**Model Name:** `Jackrong/Qwen3.5-9B-GLM5.1-Distill-v1`
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**Base Model:** Qwen3.5-9B
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**Training Type:** Supervised Fine-Tuning (SFT, Distillation)
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**Parameter Scale:** 9B
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**Training Framework:** Unsloth
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This model is a distilled variant of **Qwen3.5-9B**, trained on high-quality reasoning data derived from **GLM-5.1**.
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The primary goals are to:
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- Improve **structured reasoning ability**
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- Enhance **instruction-following consistency**
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- Activate **latent knowledge via better reasoning structure**
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## 📊 Training Data
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### Main Dataset
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- `Jackrong/GLM-5.1-Reasoning-1M-Cleaned`
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- Cleaned from the original `Kassadin88/GLM-5.1-1000000x` dataset.
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- Generated from a **GLM-5.1 teacher model**
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- Approximately **700x** the scale of `Qwen3.5-reasoning-700x`
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- Training used a **filtered subset**, not the full source dataset.
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### Auxiliary Dataset
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- `Jackrong/Qwen3.5-reasoning-700x`
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...
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description: "# \U0001FA90 Qwen3.5-9B-GLM5.1-Distill-v1\n\n## \U0001F4CC Model Overview\n\n**Model Name:** `Jackrong/Qwen3.5-9B-GLM5.1-Distill-v1`\n**Base Model:** Qwen3.5-9B\n**Training Type:** Supervised Fine-Tuning (SFT, Distillation)\n**Parameter Scale:** 9B\n**Training Framework:** Unsloth\n\nThis model is a distilled variant of **Qwen3.5-9B**, trained on high-quality reasoning data derived from **GLM-5.1**.\n\nThe primary goals are to:\n\n - Improve **structured reasoning ability**\n - Enhance **instruction-following consistency**\n - Activate **latent knowledge via better reasoning structure**\n\n## \U0001F4CA Training Data\n\n### Main Dataset\n\n - `Jackrong/GLM-5.1-Reasoning-1M-Cleaned`\n - Cleaned from the original `Kassadin88/GLM-5.1-1000000x` dataset.\n - Generated from a **GLM-5.1 teacher model**\n - Approximately **700x** the scale of `Qwen3.5-reasoning-700x`\n - Training used a **filtered subset**, not the full source dataset.\n\n### Auxiliary Dataset\n\n - `Jackrong/Qwen3.5-reasoning-700x`\n\n...\n"
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license: "apache-2.0"
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tags:
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- llm
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@@ -127,26 +94,7 @@
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url: "github:mudler/LocalAI/gallery/virtual.yaml@master"
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urls:
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- https://huggingface.co/hesamation/Qwen3.6-35B-A3B-Claude-4.6-Opus-Reasoning-Distilled-GGUF
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description: |
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# 🔥 Qwen3.6-35B-A3B-Claude-4.6-Opus-Reasoning-Distilled
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A reasoning SFT fine-tune of `Qwen/Qwen3.6-35B-A3B` on chain-of-thought (CoT) distillation mostly sourced from Claude Opus 4.6. The goal is to preserve Qwen3.6's strong agentic coding and reasoning base while nudging the model toward structured Claude Opus-style reasoning traces and more stable long-form problem solving.
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The training path is text-only. The Qwen3.6 base architecture includes a vision encoder, but this fine-tuning run did not train on image or video examples.
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- **Developed by:** @hesamation
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- **Base model:** `Qwen/Qwen3.6-35B-A3B`
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- **License:** apache-2.0
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This fine-tuning run is inspired by Jackrong/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled, including the notebook/training workflow style and Claude Opus reasoning-distillation direction.
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[](https://x.com/Hesamation) [](https://discord.gg/vtJykN3t)
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## Benchmark Results
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The MMLU-Pro pass used 70 total questions per model: `--limit 5` across 14 MMLU-Pro subjects. Treat this as a smoke/comparative check, not a release-quality full benchmark.
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...
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description: "# \U0001F525 Qwen3.6-35B-A3B-Claude-4.6-Opus-Reasoning-Distilled\n\nA reasoning SFT fine-tune of `Qwen/Qwen3.6-35B-A3B` on chain-of-thought (CoT) distillation mostly sourced from Claude Opus 4.6. The goal is to preserve Qwen3.6's strong agentic coding and reasoning base while nudging the model toward structured Claude Opus-style reasoning traces and more stable long-form problem solving.\n\nThe training path is text-only. The Qwen3.6 base architecture includes a vision encoder, but this fine-tuning run did not train on image or video examples.\n\n - **Developed by:** @hesamation\n - **Base model:** `Qwen/Qwen3.6-35B-A3B`\n - **License:** apache-2.0\n\nThis fine-tuning run is inspired by Jackrong/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled, including the notebook/training workflow style and Claude Opus reasoning-distillation direction.\n\n[](https://x.com/Hesamation) [](https://discord.gg/vtJykN3t)\n\n## Benchmark Results\n\nThe MMLU-Pro pass used 70 total questions per model: `--limit 5` across 14 MMLU-Pro subjects. Treat this as a smoke/comparative check, not a release-quality full benchmark.\n\n...\n"
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license: "apache-2.0"
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tags:
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- llm
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@@ -182,40 +130,7 @@
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url: "github:mudler/LocalAI/gallery/virtual.yaml@master"
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urls:
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- https://huggingface.co/Jackrong/Qwen3.5-9B-GLM5.1-Distill-v1-GGUF
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description: |
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# 🪐 Qwen3.5-9B-GLM5.1-Distill-v1
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## 📌 Model Overview
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**Model Name:** `Jackrong/Qwen3.5-9B-GLM5.1-Distill-v1`
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**Base Model:** Qwen3.5-9B
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**Training Type:** Supervised Fine-Tuning (SFT, Distillation)
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**Parameter Scale:** 9B
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**Training Framework:** Unsloth
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This model is a distilled variant of **Qwen3.5-9B**, trained on high-quality reasoning data derived from **GLM-5.1**.
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The primary goals are to:
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- Improve **structured reasoning ability**
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- Enhance **instruction-following consistency**
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- Activate **latent knowledge via better reasoning structure**
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## 📊 Training Data
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### Main Dataset
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- `Jackrong/GLM-5.1-Reasoning-1M-Cleaned`
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- Cleaned from the original `Kassadin88/GLM-5.1-1000000x` dataset.
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- Generated from a **GLM-5.1 teacher model**
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- Approximately **700x** the scale of `Qwen3.5-reasoning-700x`
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- Training used a **filtered subset**, not the full source dataset.
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### Auxiliary Dataset
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- `Jackrong/Qwen3.5-reasoning-700x`
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...
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description: "# \U0001FA90 Qwen3.5-9B-GLM5.1-Distill-v1\n\n## \U0001F4CC Model Overview\n\n**Model Name:** `Jackrong/Qwen3.5-9B-GLM5.1-Distill-v1`\n**Base Model:** Qwen3.5-9B\n**Training Type:** Supervised Fine-Tuning (SFT, Distillation)\n**Parameter Scale:** 9B\n**Training Framework:** Unsloth\n\nThis model is a distilled variant of **Qwen3.5-9B**, trained on high-quality reasoning data derived from **GLM-5.1**.\n\nThe primary goals are to:\n\n - Improve **structured reasoning ability**\n - Enhance **instruction-following consistency**\n - Activate **latent knowledge via better reasoning structure**\n\n## \U0001F4CA Training Data\n\n### Main Dataset\n\n - `Jackrong/GLM-5.1-Reasoning-1M-Cleaned`\n - Cleaned from the original `Kassadin88/GLM-5.1-1000000x` dataset.\n - Generated from a **GLM-5.1 teacher model**\n - Approximately **700x** the scale of `Qwen3.5-reasoning-700x`\n - Training used a **filtered subset**, not the full source dataset.\n\n### Auxiliary Dataset\n\n - `Jackrong/Qwen3.5-reasoning-700x`\n\n...\n"
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license: "apache-2.0"
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tags:
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- llm
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@@ -3845,7 +3760,7 @@
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cached in the models directory like any other managed model).
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NON-COMMERCIAL RESEARCH USE ONLY. For commercial use see `insightface-opencv`.
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tags: [face-recognition, face-verification, face-embedding, research-only, gpu, cpu]
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urls: [https://github.com/deepinsight/insightface]
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urls: ['https://github.com/deepinsight/insightface']
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overrides:
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backend: insightface
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parameters: {model: insightface-buffalo-l}
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@@ -3876,7 +3791,7 @@
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cheaper detector — good balance on mid-range hardware.
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NON-COMMERCIAL RESEARCH USE ONLY.
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tags: [face-recognition, face-verification, face-embedding, research-only, gpu, cpu]
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urls: [https://github.com/deepinsight/insightface]
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urls: ['https://github.com/deepinsight/insightface']
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overrides:
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backend: insightface
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parameters: {model: insightface-buffalo-m}
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@@ -3906,7 +3821,7 @@
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genderage, ~159MB). Good fit for mid-range CPU deployments.
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NON-COMMERCIAL RESEARCH USE ONLY.
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tags: [face-recognition, face-verification, face-embedding, research-only, edge, cpu]
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urls: [https://github.com/deepinsight/insightface]
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urls: ['https://github.com/deepinsight/insightface']
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overrides:
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backend: insightface
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parameters: {model: insightface-buffalo-s}
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@@ -3938,7 +3853,7 @@
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only verification and embedding are needed.
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NON-COMMERCIAL RESEARCH USE ONLY.
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tags: [face-recognition, face-verification, face-embedding, research-only, edge, cpu]
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urls: [https://github.com/deepinsight/insightface]
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urls: ['https://github.com/deepinsight/insightface']
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overrides:
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backend: insightface
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parameters: {model: insightface-buffalo-sc}
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@@ -3969,7 +3884,7 @@
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harder benchmarks; pays for it in GPU memory.
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NON-COMMERCIAL RESEARCH USE ONLY.
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tags: [face-recognition, face-verification, face-embedding, research-only, gpu]
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urls: [https://github.com/deepinsight/insightface]
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urls: ['https://github.com/deepinsight/insightface']
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overrides:
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backend: insightface
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parameters: {model: insightface-antelopev2}
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@@ -4001,7 +3916,7 @@
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Weights are downloaded on install via LocalAI's gallery mechanism
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(~40MB).
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tags: [face-recognition, face-verification, face-embedding, commercial-ok, gpu, cpu]
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urls: [https://github.com/opencv/opencv_zoo]
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urls: ['https://github.com/opencv/opencv_zoo']
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overrides:
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backend: insightface
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parameters: {model: face_detection_yunet_2023mar.onnx}
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@@ -4035,7 +3950,7 @@
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at comparable accuracy for face tasks. APACHE 2.0 — commercial-safe.
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Weights are downloaded on install via LocalAI's gallery mechanism.
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tags: [face-recognition, face-verification, face-embedding, commercial-ok, edge, cpu]
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urls: [https://github.com/opencv/opencv_zoo]
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urls: ['https://github.com/opencv/opencv_zoo']
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overrides:
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backend: insightface
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parameters: {model: face_detection_yunet_2023mar_int8.onnx}
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@@ -15923,6 +15838,7 @@
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uri: "https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/vae/wan_2.1_vae.safetensors"
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- filename: "umt5-xxl-encoder-Q8_0.gguf"
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uri: "huggingface://city96/umt5-xxl-encoder-gguf/umt5-xxl-encoder-Q8_0.gguf"
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sha256: 2521d4de0bf9e1cc6549866463ceae85e4ec3239bc6063f7488810be39033bbc
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- filename: "clip_vision_h.safetensors"
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uri: "https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/clip_vision/clip_vision_h.safetensors"
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- name: sd-1.5-ggml
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