metadata
base_model: nomic-ai/nomic-embed-text-v1.5
library_name: sentence-transformers
pipeline_tag: sentence-similarity
license: apache-2.0
model_creator: nomic-ai
quantized_by: Second State Inc.
language: en
Nomic-embed-text-v1.5-Embedding-GGUF
Original Model
nomic-ai/nomic-embed-text-v1.5
Run with LlamaEdge
LlamaEdge version: v0.14.17
Prompt template
- Prompt type:
embedding
- Prompt type:
Context size:
768
Run as LlamaEdge service
wasmedge --dir .:. --nn-preload default:GGML:AUTO:nomic-embed-text-v1.5-f16.gguf \ llama-api-server.wasm \ --prompt-template embedding \ --ctx-size 768 \ --model-name nomic-embed-text-v1.5
Quantized GGUF Models
Name | Quant method | Bits | Size | Use case |
---|---|---|---|---|
nomic-embed-text-v1.5-Q2_K.gguf | Q2_K | 2 | 60.8 MB | smallest, significant quality loss - not recommended for most purposes |
nomic-embed-text-v1.5-Q3_K_L.gguf | Q3_K_L | 3 | 80.6 MB | small, substantial quality loss |
nomic-embed-text-v1.5-Q3_K_M.gguf | Q3_K_M | 3 | 76.2 MB | very small, high quality loss |
nomic-embed-text-v1.5-Q3_K_S.gguf | Q3_K_S | 3 | 68.7 MB | very small, high quality loss |
nomic-embed-text-v1.5-Q4_0.gguf | Q4_0 | 4 | 83.7 MB | legacy; small, very high quality loss - prefer using Q3_K_M |
nomic-embed-text-v1.5-Q4_K_M.gguf | Q4_K_M | 4 | 90.0 MB | medium, balanced quality - recommended |
nomic-embed-text-v1.5-Q4_K_S.gguf | Q4_K_S | 4 | 84.0 MB | small, greater quality loss |
nomic-embed-text-v1.5-Q5_0.gguf | Q5_0 | 5 | 97.9 MB | legacy; medium, balanced quality - prefer using Q4_K_M |
nomic-embed-text-v1.5-Q5_K_M.gguf | Q5_K_M | 5 | 103 MB | large, very low quality loss - recommended |
nomic-embed-text-v1.5-Q5_K_S.gguf | Q5_K_S | 5 | 97.9 MB | large, low quality loss - recommended |
nomic-embed-text-v1.5-Q6_K.gguf | Q6_K | 6 | 113 MB | very large, extremely low quality loss |
nomic-embed-text-v1.5-Q8_0.gguf | Q8_0 | 8 | 146 MB | very large, extremely low quality loss - not recommended |
nomic-embed-text-v1.5-f16.gguf | f16 | 16 | 274 MB | very large, extremely low quality loss - not recommended |
Quantized with llama.cpp b4120