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Joseph

Joseph717171
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reacted to merve's post with ❤️ about 17 hours ago
there's a new multimodal retrieval model in town 🤠 LlamaIndex released vdr-2b-multi-v1 > uses 70% less image tokens, yet outperforming other dse-qwen2 based models > 3x faster inference with less VRAM 💨 > shrinkable with matryoshka 🪆 > can do cross-lingual retrieval! Collection: https://huggingface.co/collections/llamaindex/visual-document-retrieval-678151d19d2758f78ce910e1 (with models and datasets) Demo: https://huggingface.co/spaces/llamaindex/multimodal_vdr_demo Learn more from their blog post here https://huggingface.co/blog/vdr-2b-multilingual 📖
updated a model 4 days ago
Joseph717171/Hermes-3-Llama-3.1-8B-OQ8_0-F32.EF32.IQ4_K-Q8_0-GGUF
updated a model 5 days ago
Joseph717171/Models
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GGUF Llama-3.2-Instruct-OQ8_0-F32.EF32.IQ4_K-Q8_0 IQuants
Custom GGUF quants of Meta’s Llama-3.2-Instruct's finetunes, where the Output Tensors are quantized to Q8_0 or F32 and the Embeddings are kept @F32
GGUF LLaMa-3.1-8B-Instruct-Based OQ8_0.EF32 IQuants
Custom GGUF quants of Llama-3.1-8B-Instruct fine-tunes, where the Output Tensors are quantized to Q8_0 while the Embeddings are kept at F32. 🧠🔥🚀

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