GraySoft
Download guIDE →
Model Comparison

ggml-org/embeddinggemma-300m-qat-q8_0-ggufvsvlsav/vikhr-nemo-12b-instruct-r-21-09-24-q8_0-gguf

Side-by-side comparison of ggml-org/embeddinggemma-300m-qat-q8_0-gguf and vlsav/vikhr-nemo-12b-instruct-r-21-09-24-q8_0-gguf: downloads, license, context length, tasks, and benchmarks.

ggml-org/embeddinggemma-300m-qat-q8_0-gguf

ggml-org · feature-extraction

# embeddinggemma-300m-qat-q8_0 GGUF Recommended way to run this model: ``sh llama-server -hf ggml-org/embeddinggemma-300m-qat-q8_0-GGUF --embeddings ` Then the endpoint can be accessed at http://localhost:8080/embedding, for example using curl: `console curl --request POST \ --u…

vlsav/vikhr-nemo-12b-instruct-r-21-09-24-q8_0-gguf

VlSav · —

This model was converted to GGUF format from Vikhrmodels/Vikhr-Nemo-12B-Instruct-R-21-09-24 using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

Side-by-side Specifications

ggml-org/embeddinggemma-300m-qat-q8_0-ggufvlsav/vikhr-nemo-12b-instruct-r-21-09-24-q8_0-gguf
Authorggml-orgVlSav
Pipeline Taskfeature-extraction—
Librarysentence-transformers—
Downloads47,806134,084
Likes154
LicenseUnknownUnknown
Context Length——
Created2025-09-042024-09-22
Last Modified2025-09-152024-09-22
Tags
sentence-transformersggufsentence-similarityfeature-extractionbase_model:google/embeddinggemma-300m-qat-q8_0-unquantizedbase_model:quantized:google/embeddinggemma-300m-qat-q8_0-unquantizedlicense:gemmaendpoints_compatibleregion:us
ggufllama-cppgguf-my-repoenrudataset:Vikhrmodels/GrandMaster-PRO-MAXdataset:Vikhrmodels/Grounded-RAG-RU-v2base_model:Vikhrmodels/Vikhr-Nemo-12B-Instruct-R-21-09-24base_model:quantized:Vikhrmodels/Vikhr-Nemo-12B-Instruct-R-21-09-24license:apache-2.0

View full details: ggml-org/embeddinggemma-300m-qat-q8_0-gguf · vlsav/vikhr-nemo-12b-instruct-r-21-09-24-q8_0-gguf