v0.43.0

Deprecation notice.

README.md

@@ -1,73 +1,10 @@
+
 ---
 library_name: pytorch
-license: unknown
+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/allam_7b/web-assets/model_demo.png)
-
-# ALLaM-7B: Optimized for Mobile Deployment
-## Large Language Model supporting Arabic and English
-
-ALLaM 7B is SDAIA's first generation edge model, optimized for performance on Snapdragon X Elite.
-
- More details on model performance across various devices, can be found [here](https://aihub.qualcomm.com/models/allam_7b).
-
-**WARNING**: The model assets are not readily available for download due to licensing restrictions.
-
-### Model Details
-
-- **Model Type:** Model_use_case.text_generation
-- **Model Stats:**
-  - Input sequence length for Prompt Processor: 128
-  - Max context length: 1024
-  - Num of key-value heads: 32
-  - Number of parameters: 7B
-  - Precision: w4a16 + w8a16 (few layers)
-  - Use: Initiate conversation with prompt-processor and then token generator for subsequent iterations.
-  - Minimum QNN SDK version required: 2.28.2
-  - Supported languages: English, Arabic.
-  - 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)
-|---|---|---|---|---|---|
-| ALLaM-7B | w4a16 | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN_CONTEXT_BINARY | 9.5 | 0.23854499999999998 - 1.399168 | -- | -- |
-
-## Deploy Allam 7B on Snapdragon X Elite NPU
-
-Please follow the [LLM on-device deployment](https://github.com/quic/ai-hub-apps/tree/main/tutorials/llm_on_genie) tutorial.
-
-
-
-
-
-## 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.