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
- Downloads last month
- 5
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API:
The model authors have turned it off explicitly.
Model tree for dewdev/bling-tiny-llama-onnx
Base model
llmware/bling-tiny-llama-v0