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models.json
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128 lines (128 loc) · 4.39 KB
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[
{
"name": "SAM3 (Segment Anything 3)",
"repo_id": "facebook/sam3",
"folder": "sam3",
"description": "Required for Masking. GATED MODEL: Requires HF Token.",
"gated": true
},
{
"name": "Qwen2.5-VL-3B-Instruct",
"repo_id": "Qwen/Qwen2.5-VL-3B-Instruct",
"folder": "Qwen2.5-VL-3B-Instruct",
"description": "Smallest current generation. Fast, good for low VRAM (6GB+).",
"gated": false
},
{
"name": "Qwen2.5-VL-3B-Abliterated",
"repo_id": "huihui-ai/Qwen2.5-VL-3B-Instruct-abliterated",
"folder": "Qwen2.5-VL-3B-Instruct-abliterated",
"description": "Uncensored/Abliterated version of 3B.",
"gated": false
},
{
"name": "Qwen2.5-VL-7B-Instruct",
"repo_id": "Qwen/Qwen2.5-VL-7B-Instruct",
"folder": "Qwen2.5-VL-7B-Instruct",
"description": "Standard size. Best balance of quality and speed.",
"gated": false
},
{
"name": "Qwen2.5-VL-7B-Abliterated",
"repo_id": "huihui-ai/Qwen2.5-VL-7B-Instruct-Abliterated",
"folder": "Qwen2.5-VL-7B-Instruct-Abliterated",
"description": "Uncensored/Abliterated version of 7B.",
"gated": false
},
{
"name": "Qwen2.5-VL-7B-Caption-It",
"repo_id": "prithivMLmods/Qwen2.5-VL-7B-Abliterated-Caption-it",
"folder": "Qwen2.5-VL-7B-Abliterated-Caption-it",
"description": "Fine-tuned specifically for captioning.",
"gated": false
},
{
"name": "Qwen3-VL-2B-Instruct",
"repo_id": "Qwen/Qwen3-VL-2B-Instruct",
"folder": "Qwen3-VL-2B-Instruct",
"description": "Next-Gen Tiny. Extremely fast.",
"gated": false
},
{
"name": "Qwen3-VL-2B-Abliterated",
"repo_id": "huihui-ai/Huihui-Qwen3-VL-2B-Instruct-abliterated",
"folder": "Qwen3-VL-2B-Instruct-abliterated",
"description": "Uncensored Next-Gen Tiny.",
"gated": false
},
{
"name": "Qwen3-VL-4B-Instruct",
"repo_id": "Qwen/Qwen3-VL-4B-Instruct",
"folder": "Qwen3-VL-4B-Instruct",
"description": "Next-Gen Small. Balanced for consumer GPUs.",
"gated": false
},
{
"name": "Qwen3-VL-4B-Abliterated",
"repo_id": "huihui-ai/Huihui-Qwen3-VL-4B-Instruct-abliterated",
"folder": "Qwen3-VL-4B-Instruct-abliterated",
"description": "Uncensored Next-Gen Small.",
"gated": false
},
{
"name": "Qwen3-VL-8B-Instruct",
"repo_id": "Qwen/Qwen3-VL-8B-Instruct",
"folder": "Qwen3-VL-8B-Instruct",
"description": "Next-Gen Standard. High quality.",
"gated": false
},
{
"name": "Qwen3-VL-8B-Abliterated",
"repo_id": "huihui-ai/Huihui-Qwen3-VL-8B-Instruct-abliterated",
"folder": "Qwen3-VL-8B-Instruct-abliterated",
"description": "Uncensored Next-Gen Standard.",
"gated": false
},
{
"name": "Qwen3-VL-32B-Instruct",
"repo_id": "Qwen/Qwen3-VL-32B-Instruct",
"folder": "Qwen3-VL-32B-Instruct",
"description": "Next-Gen Large. Very heavy, requires 24GB+ VRAM.",
"gated": false
},
{
"name": "Qwen3-VL-32B-Abliterated",
"repo_id": "huihui-ai/Huihui-Qwen3-VL-32B-Instruct-abliterated",
"folder": "Qwen3-VL-32B-Instruct-abliterated",
"description": "Uncensored Next-Gen Large.",
"gated": false
},
{
"name": "Gemma-4-E2B-it",
"repo_id": "google/gemma-4-E2B-it",
"folder": "Gemma-4-E2B-it",
"description": "Google Gemma 4. Efficient (~2.3B active params). Good for 8-12GB GPUs.",
"gated": false
},
{
"name": "Gemma-4-E4B-it",
"repo_id": "google/gemma-4-E4B-it",
"folder": "Gemma-4-E4B-it",
"description": "Google Gemma 4. ~4.5B active params. Higher quality, needs ~16GB.",
"gated": false
},
{
"name": "Gemma-4-26B-A4B-it",
"repo_id": "google/gemma-4-26B-A4B-it",
"folder": "Gemma-4-26B-A4B-it",
"description": "Google Gemma 4 MoE: 26B total, only 4B active. Fast inference, heavy VRAM.",
"gated": false
},
{
"name": "Gemma-4-31B-it",
"repo_id": "google/gemma-4-31B-it",
"folder": "Gemma-4-31B-it",
"description": "Google Gemma 4 Dense 31B. Top quality, requires 48GB+ or NF4.",
"gated": false
}
]