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gte-small-gguf
by ChristianAzinn · source Hugging Face · updated 2024-04-07
mit28 MB~1 GB RAMsource aliveunlabeled
General Text Embeddings (GTE) model. Towards General Text Embeddings with Multi-stage Contrastive Learning
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Source and license
- Source: https://huggingface.co/ChristianAzinn/gte-small-gguf
- License: mit
- Requirements: about 1 GB of RAM, 28 MB on disk (estimate: suggested file size × 1.15 + 0.5 GB; a real measurement comes with lsh models). Runs with llama.cpp.
- Tags:
sentence-transformersggufsentence-similaritySentence Transformersmtebbertfeature-extractionendeploy:azure
Numbers
- 5,929 downloads on Hugging Face
- 5 likes
- license mit
- 0.0 GB for gte-small.Q4_K_M.gguf
- 327,838 npm downloads a week for node-llama-cpp
- latest node-llama-cpp@3.22.1
Numbers as of 2026-10-02 20:59 UTC, from the source API.
Summary
Summary not ready yet: the numbers are here, the text is not. It is written by the collector through the LogiShell model facade when a provider key is present.
Reviews
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Files
| file | quant | size |
|---|---|---|
gte-small.Q2_K.gguf | Q2_K | 24 MB |
gte-small.Q3_K_L.gguf | Q3_K_L | 26 MB |
gte-small.Q3_K_M.gguf | Q3_K_M | 25 MB |
gte-small.Q3_K_S.gguf | Q3_K_S | 24 MB |
gte-small.Q4_0.gguf | Q4_0 | 25 MB |
gte-small.Q4_K_M.gguf | Q4_K_M | 28 MB |
gte-small.Q4_K_S.gguf | Q4_K_S | 27 MB |
gte-small.Q5_0.gguf | Q5_0 | 28 MB |
gte-small.Q5_K_M.gguf | Q5_K_M | 29 MB |
gte-small.Q5_K_S.gguf | Q5_K_S | 28 MB |
gte-small.Q6_K.gguf | Q6_K | 33 MB |
gte-small.Q8_0.gguf | Q8_0 | 35 MB |
gte-small_fp16.gguf | 64 MB | |
gte-small_fp32.gguf | 127 MB |
From the source README
gte-small-gguf
Model creator: thenlper
Original model: gte-small
Original Description
General Text Embeddings (GTE) model. Towards General Text Embeddings with Multi-stage Contrastive Learning
The GTE models are trained by Alibaba DAMO Academy. They are mainly based on the BERT framework and currently offer three different sizes of models, including GTE-large, GTE-base, and GTE-small. The GTE models are trained on a large-scale corpus of relevance text pairs, covering a wide range of domains and scenarios. This enables the GTE models to be applied to various downstream tasks of text embeddings, including information retrieval, semantic textual similarity, text reranking, etc.
Description
This repo contains GGUF format files for the gte-small embedding model.
These files were converted and quantized with llama.cpp PR 5500, commit 34aa045de, on a consumer RTX 4090.
This model supports up to 512 tokens of context.
Compatibility
These files are compatible with llama.cpp as of commit 4524290e8, as well as LM Studio as of version 0.2.19.
Card id model:hf:ChristianAzinn/gte-small-gguf · collected 2026-10-02 20:59 UTC · JSON