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llmware/bling-phi-3-onnx

By llmware · ↓ 9 · ♥ 2 · Updated 2024-10-31

What's in this repo

This page lists the files in llmware/bling-phi-3-onnx, including model.onnx.

  • 1 ONNX models (.onnx files)
  • 12 files, including 7 .json, 1 .md, 1 .onnx, 1 .data, 1 .model
  • Last updated 2024-10-31

ONNX files

File Size Download
model.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

bling-phi-3-onnx

bling-phi-3-onnx is a fast and accurate 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 most accurate in the BLING/DRAGON model series, which is especially notable given the relatively small size and is ideal for use on AI PCs and local inferencing.

Model Description

  • Developed by: llmware
  • Model type: phi-3
  • Parameters: 3.8 billion
  • Quantization: int4
  • Model Parent: llmware/bling-phi-3
  • Language(s) (NLP): English
  • License: Apache 2.0
  • Uses: Fact-based question-answering, RAG
  • RAG Benchmark Accuracy Score: 99.5

Model Card Contact

llmware on github
llmware on hf
llmware website

Model info

text-generation transformers
transformers onnx phi3 text-generation green llmware-rag p3 conversational custom_code base_model:llmware/bling-phi-3 base_model:quantized:llmware/bling-phi-3 license:apache-2.0
↓ 9 ♥ 2

Created: 2024-06-13

Updated: 2024-10-31

View on Hugging Face

Files (12)

.gitattributes
README.md
added_tokens.json
config.json
genai_config.json
hash_record_sha256.json
model.onnx ONNX
model.onnx.data
special_tokens_map.json
tokenizer.json
tokenizer.model
tokenizer_config.json

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