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LocalAI-io/Llama-3-Kimodo-GGML

sourceHugging Faceotherupdated 5d agoView on Hugging Face

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Llama-3-Kimodo-GGML

Native GGML/GGUF text encoder used by Kimodo. This is the reusable LLM2Vec encoder only; download a matching Kimodo diffusion model separately, for example `Kimodo-SMPLX-RP-v1-GGML`.

From a kimodo.cpp checkout with the Hugging Face CLI installed, install both with:

scripts/download_gguf_weights.sh --output "$PWD"

The downloader installs the recommended Q80 variant by default. Select a different one with `--text-quantization bf16|q80|q6k|q5k|q4k|q4k_m. Every variant is one monolithic weight GGUF and uses the same tokenizer.gguf`. Kimodo reads individual tensor ranges from the monolith, so streaming one layer at a time does not require separate per-layer files.

Variant	Weight file	Size (GB)	Intended use
BF16	`Llama-3-Kimodo-BF16.gguf`	15.18	Reference
Q8_0	`Llama-3-Kimodo-Q8_0.gguf`	8.14	Recommended
Q6_K	`Llama-3-Kimodo-Q6_K.gguf`	6.32	Experimental
Q5_K	`Llama-3-Kimodo-Q5_K.gguf`	5.33	Experimental
Q4_K	`Llama-3-Kimodo-Q4_K.gguf`	4.39	Experimental
Q4KM	`Llama-3-Kimodo-Q4_K_M.gguf`	5.06	Preferred low-bit experiment

The legacy split BF16 tree remains temporarily available for older clients.

Provenance and licence

The bundle is converted from Meta Llama-3-8B-Instruct and the MIT-licensed McGill LLM2Vec MNTP and supervised adapters. Built with Meta Llama 3.

LICENSE-META-LLAMA-3.txt and NOTICE accompany this distribution. Review the Meta Llama 3 Community License before use or redistribution. MANIFEST.json records the exact source commits and SHA-256 of every published artifact, plus the weight/tokenizer mapping for each quantization.