Model Intelligence Sheet
psipi/liuhaotian_llava-v1.5-13b-gguf overview
Comprehensive model page for psipi/liuhaotian_llava-v1.5-13b-gguf
Downloads
657
Likes
37
Pipeline
image-text-to-text
Library
—
Visibility
Public
Access
Open
Repository Files & Downloads
10 files detected
Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| llava-v1.5-13b-Q2_K.gguf | GGUF | Q2_K | 5.06 GB | Download |
| llava-v1.5-13b-Q4_0.gguf | GGUF | — | 6.86 GB | Download |
| llava-v1.5-13b-Q5_K_M.gguf | GGUF | Q5_K_M | 8.60 GB | Download |
| llava-v1.5-13b-Q6_K.gguf | GGUF | Q6_K | 9.95 GB | Download |
| llava-v1.5-13b-Q8_0.gguf | GGUF | — | 12.88 GB | Download |
| llava-v1.5-13b-f16.gguf | GGUF | F16 | 24.25 GB | Download |
| mmproj-model-Q4_0.gguf | GGUF | — | 174.83 MB | Download |
| mmproj-model-Q5_0.gguf | GGUF | — | 328.11 MB | Download |
| mmproj-model-Q8_0.gguf | GGUF | — | 232.31 MB | Download |
| mmproj-model-f16.gguf | GGUF | F16 | 615.51 MB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
{
"metadata": {},
"card_data": {
"tags": [
"llava"
],
"pipeline_tag": "image-text-to-text",
"frontmatter": {
"tags": [
"llava"
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"pipeline_tag": "image-text-to-text"
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"hero_image_url": "https://cdn-uploads.huggingface.co/production/uploads/64a22257d3149e05bc6d259f/QuoYvv46QmwgAS6d3LYxj.png",
"summary": "",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\ntags:\n- llava\npipeline_tag: image-text-to-text\n---\n\n---\ninference: false\n---\n\n<br>\n<br>\n\n# LLaVA Model Card\n\n## Model details\n\n**Model type:**\nLLaVA is an open-source chatbot trained by fine-tuning LLaMA/Vicuna on GPT-generated multimodal instruction-following data.\nIt is an auto-regressive language model, based on the transformer architecture.\n\n**Model date:**\nLLaVA-v1.5-13B was trained in September 2023.\n\n**Paper or resources for more information:**\nhttps://llava-vl.github.io/\n\n## License\nLlama 2 is licensed under the LLAMA 2 Community License, \nCopyright (c) Meta Platforms, Inc. All Rights Reserved.\n\n**Where to send questions or comments about the model:**\nhttps://github.com/haotian-liu/LLaVA/issues\n\n## Intended use\n**Primary intended uses:**\nThe primary use of LLaVA is research on large multimodal models and chatbots.\n\n**Primary intended users:**\nThe primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence.\n\n## Training dataset\n- 558K filtered image-text pairs from LAION/CC/SBU, captioned by BLIP.\n- 158K GPT-generated multimodal instruction-following data.\n- 450K academic-task-oriented VQA data mixture.\n- 40K ShareGPT data.\n\n## Evaluation dataset\nA collection of 12 benchmarks, including 5 academic VQA benchmarks and 7 recent benchmarks specifically proposed for instruction-following LMMs.\n\n\nllava-v1.5-13b-GGUF\n\nThis repo contains GGUF files to inference llava-v1.5-13b with llama.cpp end-to-end without any extra dependency.\nstirred by twobob\nNote: The mmproj-model-f16.gguf file structure is experimental and may change. Always use the latest code in llama.cpp.\n\nprops to @mys\n\n\n\n\n",
"related_quantizations": []
},
"tags": [
"gguf",
"llava",
"image-text-to-text",
"endpoints_compatible",
"region:us"
],
"likes": 37,
"downloads": 657,
"gated": false,
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"last_modified": "2024-03-11T19:31:57.000Z",
"created_at": "2023-12-01T14:23:26.000Z",
"pipeline_tag": "image-text-to-text",
"library_name": ""
}
Source payload excerpt (from Hugging Face API)
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"author": "PsiPi",
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