baai/bunny-llama-3-8b-v-gguf - Free GGUF Download is indexed on GraySoft with repository links, GGUF quant files, and Hugging Face metadata. This page helps you pick a local model for guIDE or other runtimes. See related models in the same shard below.
baai/bunny-llama-3-8b-v-gguf overview
๐ Technical report | ๐ Code | ๐ฐ Demo This is GGUF format of Bunny-Llama-3-8B-V. Bunny is a family of lightweight but powerful multimodal models. It offers multiple plug-and-play vision encoders, like EVA-CLIP, SigLIP and language backbones, including Llama-3-8B, Phi-1.5, StableLM-2, Qwen1.5, MiniCPM and Phi-2. To compensate for the decrease in model size, we construct more informative training data by curated selection from a broader data source. We provide Bunny-Llama-3-8B-V, which is built upon SigLIP and Llama-3-8B-Instruct. More details about this model can be found in GitHub. !comparison # Quickstart
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Normalized metadata (stored in metadata_json)
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"metadata": {},
"card_data": {
"inference": false,
"license": "apache-2.0",
"frontmatter": {
"inference": "false",
"license": "apache-2.0"
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"hero_image_url": "./icon.png",
"summary": "๐ Technical report | ๐ Code | ๐ฐ Demo This is **GGUF** format of Bunny-Llama-3-8B-V. Bunny is a family of lightweight but powerful multimodal models. It offers multiple plug-and-play vision encoders, like EVA-CLIP, SigLIP and language backbones, including Llama-3-8B, Phi-1.5, StableLM-2, Qwen1.5, MiniCPM and Phi-2. To compensate for the decrease in model size, we construct more informative training data by curated selection from a broader data source. We provide Bunny-Llama-3-8B-V, which is built upon SigLIP and Llama-3-8B-Instruct. More details about this model can be found in GitHub. !comparison # Quickstart",
"quick_links": [],
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"readme_markdown": "---\ninference: false\nlicense: apache-2.0\n---\n\n# Model Card\n\n<p align=\"center\">\n <img src=\"./icon.png\" alt=\"Logo\" width=\"350\">\n</p>\n\n๐ [Technical report](https://arxiv.org/abs/2402.11530) | ๐ [Code](https://github.com/BAAI-DCAI/Bunny) | ๐ฐ [Demo](http://bunny.baai.ac.cn)\n\nThis is **GGUF** format of [Bunny-Llama-3-8B-V](https://huggingface.co/BAAI/Bunny-Llama-3-8B-V).\n\nBunny is a family of lightweight but powerful multimodal models. It offers multiple plug-and-play vision encoders, like EVA-CLIP, SigLIP and language backbones, including Llama-3-8B, Phi-1.5, StableLM-2, Qwen1.5, MiniCPM and Phi-2. To compensate for the decrease in model size, we construct more informative training data by curated selection from a broader data source.\n\nWe provide Bunny-Llama-3-8B-V, which is built upon [SigLIP](https://huggingface.co/google/siglip-so400m-patch14-384) and [Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct). More details about this model can be found in [GitHub](https://github.com/BAAI-DCAI/Bunny).\n\n\n\n\n# Quickstart\n\n## Chat by [`llama.cpp`](https://github.com/ggerganov/llama.cpp)\n\n```shell\n# sample images can be found in images folder\n\n# fp16\n./llava-cli -m ggml-model-f16.gguf --mmproj mmproj-model-f16.gguf --image example_2.png -c 4096 -e \\\n -p \"A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>\\nWhy is the image funny? ASSISTANT:\" \\\n --temp 0.0\n\n# int4\n./llava-cli -m ggml-model-Q4_K_M.gguf --mmproj mmproj-model-f16.gguf --image example_2.png -c 4096 -e \\\n -p \"A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>\\nWhy is the image funny? ASSISTANT:\" \\\n --temp 0.0\n```\n\n## Chat by [ollama](https://ollama.com/)\n\n```shell\n# sample images can be found in images folder\n\n# fp16\nollama create Bunny-Llama-3-8B-V-fp16 -f ./ollama-f16\nollama run Bunny-Llama-3-8B-V-fp16 'example_2.png\nWhy is the image funny?'\n\n# int4\nollama create Bunny-Llama-3-8B-V-int4 -f ./ollama-Q4_K_M\nollama run Bunny-Llama-3-8B-V-int4 'example_2.png\nWhy is the image funny?'\n```\n\n",
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Source payload excerpt (from Hugging Face API)
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