v0.33.0

See https://github.com/quic/ai-hub-models/releases/v0.33.0 for changelog.

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+DEPLOYMENT_MODEL_LICENSE.pdf filter=lfs diff=lfs merge=lfs -text

DEPLOYMENT_MODEL_LICENSE.pdf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4409f93b0e82531303b3e10f52f1fdfb56467a25f05b7441c6bbd8bb8a64b42c
+size 109629

LICENSE

@@ -0,0 +1,2 @@
+The license of the original trained model can be found at https://huggingface.co/microsoft/Phi-3.5-mini-instruct/blob/main/LICENSE.
+The license for the deployable model files (.tflite, .onnx, .dlc, .bin, etc.) can be found in DEPLOYMENT_MODEL_LICENSE.pdf.

README.md

@@ -28,7 +28,7 @@ This model is an implementation of Phi-3.5-mini-instruct found [here](https://hu
 - **Model Stats:**
   - Input sequence length for Prompt Processor: 128
   - Context length: 4096
-  - Number of parameters: None
+  - Number of parameters: 3.8B
   - Precision: w4a16 + w8a16 (few layers)
   - Num of key-value heads: 8
   - Information about the model parts: Prompt Processor and Token Generator are split into 4 parts each. Each corresponding Prompt Processor and Token Generator part share weights.