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This repository is an **Ente-operated, byte-for-byte mirror** of a single upstream GGUF artifact. It exists so that Ensu's on-device retrieval feature can download its shared embedding model directly, while remaining exactly compatible with the published Ensu knowledge packs. Ente has **not** modified, re-converted, re-quantized, or repacked the GGUF file. See `MODIFICATIONS.md` for the modification disclosure and `PROVENANCE.json` for machine-readable provenance. The GGUF Q8_0 artifact is a converted/quantized derivative of `google/embeddinggemma-300m`; the conversion was published upstream by ggml-org.

Embeddings & similarity
Input Text→ Output Embedding
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Jun 9 Update: Added MTP support. See our MTP Guide . Apr 11 Update: Re-download for Google's latest chat template and llama.cpp fixes. Gemma 4 can now be run and fine-tuned in Unsloth Studio . Read our guide . See all versions of Gemma 4 (GGUF, 16-bit etc.) in our collection . Example of Gemma 4 E4B (4-bit GGUF) running in Unsloth Studio with tool-calling: Gemma is a family of open models built by Google DeepMind. Gemma 4 models are multimodal, handling text and image input (with audio supported on small models) and generating text output. This release includes open-weights models in both pre-trained and instruction-tuned variants. Gemma 4 features a context window of up to 256K tokens and maintains multilingual support in over 140 languages. Featuring both Dense and Mixture-of-Experts (MoE) architectures, Gemma 4 is well-suited for tasks like text generation, coding, and reasoning. The models are available in four distinct sizes: **E2B**, **E4B**, **26B A4B**, and **31B**. Their diverse sizes make them deployable in environments ranging from high-end phones to laptops and servers, democratizing access to state-of-the-art AI.

Visual QA
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Jun 9 Update: Added MTP support. See our MTP Guide . Apr 11 Update: Re-download for Google's latest chat template and llama.cpp fixes. Gemma 4 can now be run and fine-tuned in Unsloth Studio . Read our guide . See all versions of Gemma 4 (GGUF, 16-bit etc.) in our collection . Example of Gemma 4 E4B (4-bit GGUF) running in Unsloth Studio with tool-calling: Gemma is a family of open models built by Google DeepMind. Gemma 4 models are multimodal, handling text and image input (with audio supported on small models) and generating text output. This release includes open-weights models in both pre-trained and instruction-tuned variants. Gemma 4 features a context window of up to 256K tokens and maintains multilingual support in over 140 languages. Featuring both Dense and Mixture-of-Experts (MoE) architectures, Gemma 4 is well-suited for tasks like text generation, coding, and reasoning. The models are available in four distinct sizes: **E2B**, **E4B**, **26B A4B**, and **31B**. Their diverse sizes make them deployable in environments ranging from high-end phones to laptops and servers, democratizing access to state-of-the-art AI.

Visual QA
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Find more details in the original model card: https://huggingface.co/LiquidAI/LFM2.5-VL-1.6B Then you can type `/image ` to add an image to the chat, then ask `What is in the image?` or any other question about the image. - Got questions or want to connect? Join our Discord community - If you are interested in custom solutions with edge deployment, please contact our sales team.

Visual QA
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Separate input, output and cache rates, then estimate the same workload. Image, audio and video rates may use items, duration or resolution rather than tokens.

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Not necessarily. Check each version’s license, commercial restrictions and policies. Self-hosting also incurs compute and maintenance costs.

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