llmware/slim-extract-phi-3-onnx
By llmware · ↓ 0 · ♥ 1 · Updated 2024-10-31
What's in this repo
This page lists the files in llmware/slim-extract-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
slim-extract-phi-3-onnx
slim-extract-phi-3-onnx is a specialized function calling model with a single mission to look for values in a text, based on an "extract" key that is passed as a parameter. No other instructions are required except to pass the context passage, and the target key, and the model will generate a python dictionary consisting of the extract key and a list of the values found in the text, including an 'empty list' if the text does not provide an answer for the value of the selected key.
This is an ONNX int4 quantized version of slim-extract-phi-3, providing a fast, high-quality inference implementation, optimized for AI PCs using Intel GPU, CPU and NPU.
Model Description
- Developed by: llmware
- Model type: phi-3
- Parameters: 3.8 billion
- Model Parent: llmware/slim-extract-phi-3
- Language(s) (NLP): English
- License: Apache 2.0
- Uses: Extraction of values from complex business documents
- RAG Benchmark Accuracy Score: NA
- Quantization: int4
Example Usage
from llmware.models import ModelCatalog
text_passage = "The company announced that for the current quarter the total revenue increased by 9% to $125 million."
model = ModelCatalog().load_model("slim-extract-phi-3-ov")
llm_response = model.function_call(text_passage, function="extract", params=["revenue"])
Output: `llm_response = {'revenue': ['$125 million']}`
Model Card Contact
Model info
Created: 2024-10-26
Updated: 2024-10-31
View on Hugging FaceFiles (12)
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