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README.md
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license: mit
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pipeline_tag: text-generation
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tags:
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- conversational
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- custom_code
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# Phi-3 Mini-128K-Instruct ONNX model for onnxruntime-web
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1. the model is fp16 with int4 block quantization for weights
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2. the 'logits' output is fp32
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3. the model uses MHA instead of GQA
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4. onnx and external data file need to stay below 2GB to be cacheable in chromium
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---
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license: mit
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pipeline_tag: text-generation
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library_name: transformers.js
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tags:
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- ONNX
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- DML
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- ONNXRuntime
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- nlp
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- conversational
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---
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# Phi-3 Mini-128K-Instruct ONNX model for onnxruntime-web
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1. the model is fp16 with int4 block quantization for weights
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2. the 'logits' output is fp32
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3. the model uses MHA instead of GQA
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19 |
+
4. onnx and external data file need to stay below 2GB to be cacheable in chromium
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