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dewdev/bling-tiny-llama-onnx

By dewdev · ↓ 0 · ♥ 0 · Updated 2025-02-04

What's in this repo

This page lists the files in dewdev/bling-tiny-llama-onnx, including model.onnx, model_int8.onnx, model_q4.onnx and more.

  • 4 ONNX models (.onnx files)
  • 15 files, including 7 .json, 4 .onnx, 1 .md, 1 .data, 1 .model
  • Last updated 2025-02-04

ONNX files

File Size Download
model.onnx — Download
onnx/model_int8.onnx — Download
onnx/model_q4.onnx — Download
onnx/model_uint8.onnx — Download

How to use

These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.

README

cloned from llmware/bling-tiny-llama-onnx

bling-tiny-llama-onnx

bling-tiny-llama-onnx is a very small, very fast fact-based question-answering model, designed for retrieval augmented generation (RAG) with complex business documents, quantized and packaged in ONNX int4 for AI PCs using Intel GPU, CPU and NPU.

This model is one of the smallest and fastest in the series. For higher accuracy, look at larger models in the BLING/DRAGON series.

Model Description

  • Developed by: llmware
  • Model type: tinyllama
  • Parameters: 1.1 billion
  • Quantization: int4
  • Model Parent: llmware/bling-tiny-llama-v0
  • Language(s) (NLP): English
  • License: Apache 2.0
  • Uses: Fact-based question-answering, RAG
  • RAG Benchmark Accuracy Score: 86.5

Model Card Contact

llmware on github
llmware on hf
llmware website

Model info

onnx llama green llmware-rag p1 ov base_model:llmware/bling-tiny-llama-v0 base_model:quantized:llmware/bling-tiny-llama-v0 license:apache-2.0 region:us
↓ 0 ♥ 0

Created: 2025-02-04

Updated: 2025-02-04

View on Hugging Face

Files (15)

.gitattributes
README.md
config.json
genai_config.json
generation_config.json
hash_record_sha256.json
model.onnx ONNX
model.onnx.data
onnx/model_int8.onnx ONNX
onnx/model_q4.onnx ONNX
onnx/model_uint8.onnx ONNX
special_tokens_map.json
tokenizer.json
tokenizer.model
tokenizer_config.json

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