v0.44.0

Deprecation notice.

DEPLOYMENT_MODEL_LICENSE.pdf

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

LICENSE

@@ -1,2 +0,0 @@
-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

@@ -1,93 +1,10 @@
+
 ---
 library_name: pytorch
 license: other
 tags:
-- llm
-- generative_ai
-- android
-pipeline_tag: text-generation
+- deprecated
+pipeline_tag: other
 
 ---
-
-![](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/phi_3_5_mini_instruct/web-assets/model_demo.png)
-
-# Phi-3.5-Mini-Instruct: Optimized for Mobile Deployment
-## State-of-the-art large language model useful on a variety of language understanding and generation tasks
-
-
-Phi-3.5-mini is a lightweight, state-of-the-art open model built upon datasets used for Phi-3 - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data. The model belongs to the Phi-3 model family and supports 128K token context length. The model underwent a rigorous enhancement process, incorporating both supervised fine-tuning, proximal policy optimization, and direct preference optimization to ensure precise instruction adherence and robust safety measures.
-
-This model is an implementation of Phi-3.5-Mini-Instruct found [here](https://huggingface.co/microsoft/Phi-3.5-mini-instruct).
-
-
- More details on model performance across various devices, can be found [here](https://aihub.qualcomm.com/models/phi_3_5_mini_instruct).
-
-
-
-### Model Details
-
-- **Model Type:** Model_use_case.text_generation
-- **Model Stats:**
-  - Input sequence length for Prompt Processor: 128
-  - Context length: 4096
-  - 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.
-  - Prompt processor model size: 2.16 GB
-  - Token generator model size: 2.16 GB
-  - Use: Initiate conversation with prompt-processor and then token generator for subsequent iterations.
-  - Supported languages: English, Arabic, Chinese, Dutch, French, German, Italian, Russian, Spanish, Ukranian
-  - Minimum QNN SDK version required: 2.28.2
-  - TTFT: Time To First Token is the time it takes to generate the first response token. This is expressed as a range because it varies based on the length of the prompt. The lower bound is for a short prompt (up to 128 tokens, i.e., one iteration of the prompt processor) and the upper bound is for a prompt using the full context length (4096 tokens).
-  - Response Rate: Rate of response generation after the first response token.
-
-| Model | Precision | Device | Chipset | Target Runtime | Response Rate (tokens per second) | Time To First Token (range, seconds)
-|---|---|---|---|---|---|
-| Phi-3.5-Mini-Instruct | w4a16 | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 Mobile | QNN_CONTEXT_BINARY | 13.01 | 0.1469056 - 4.7009792 | -- | Use Export Script |
-| Phi-3.5-Mini-Instruct | w4a16 | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN_CONTEXT_BINARY | 6.2 | 0.185833 - 5.946656 | -- | Use Export Script |
-| Phi-3.5-Mini-Instruct | w4a16 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite Mobile | QNN_CONTEXT_BINARY | 14.73 | 0.1195948 - 3.8270336 | -- | Use Export Script |
-
-## Deploying Phi-3.5-mini-instruct on-device
-
-Please follow the [LLM on-device deployment](https://github.com/quic/ai-hub-apps/tree/main/tutorials/llm_on_genie) tutorial.
-
-
-
-## License
-* The license for the original implementation of Phi-3.5-Mini-Instruct can be found
-  [here](https://huggingface.co/microsoft/Phi-3.5-mini-instruct/blob/main/LICENSE).
-* The license for the compiled assets for on-device deployment can be found [here](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/Qualcomm+AI+Hub+Proprietary+License.pdf)
-
-
-
-## References
-* [Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone](https://arxiv.org/abs/2404.14219)
-* [Source Model Implementation](https://huggingface.co/microsoft/Phi-3.5-mini-instruct)
-
-
-
-## Community
-* Join [our AI Hub Slack community](https://qualcomm-ai-hub.slack.com/join/shared_invite/zt-2d5zsmas3-Sj0Q9TzslueCjS31eXG2UA#/shared-invite/email) to collaborate, post questions and learn more about on-device AI.
-* For questions or feedback please [reach out to us](mailto:ai-hub-support@qti.qualcomm.com).
-
-## Usage and Limitations
-
-Model may not be used for or in connection with any of the following applications:
-
-- Accessing essential private and public services and benefits;
-- Administration of justice and democratic processes;
-- Assessing or recognizing the emotional state of a person;
-- Biometric and biometrics-based systems, including categorization of persons based on sensitive characteristics;
-- Education and vocational training;
-- Employment and workers management;
-- Exploitation of the vulnerabilities of persons resulting in harmful behavior;
-- General purpose social scoring;
-- Law enforcement;
-- Management and operation of critical infrastructure;
-- Migration, asylum and border control management;
-- Predictive policing;
-- Real-time remote biometric identification in public spaces;
-- Recommender systems of social media platforms;
-- Scraping of facial images (from the internet or otherwise); and/or
-- Subliminal manipulation
+This model is deprecated. Please refer to https://aihub.qualcomm.com for the latest models and updates.