Mistral-7B-Instruct-v0_3: Optimized for Mobile Deployment
State-of-the-art large language model useful on a variety of language understanding and generation tasks
The Mistral-7B-Instruct-v0.3 Large Language Model (LLM) is an instruct fine-tuned version of the Mistral-7B-v0.3.
This is based on the implementation of Mistral-7B-Instruct-v0_3 found here. More details on model performance accross various devices, can be found here.
Model Details
- Model Type: Text generation
- Model Stats:
- Number of parameters: 7.3B
- Precision: w8a16
- Num of key-value heads: 8
- Information about the model: ['Prompt Processor and Token Generator are split into 4 parts each.', 'Each corresponding Prompt Processor and Token Generator share weights.']
- Max context length: 4096
- Prompt processor model size: 4.17 GB
- Prompt processor input: 128 tokens + KVCache initialized with pad token
- Prompt processor output: 128 output tokens + KVCache for token generator
- Token generator model size: 4.17 GB
- Token generator input: 1 input token + past KVCache
- Token generator output: 1 output token + KVCache for next iteration
- Decoding length: 4096
- Use: Initiate conversation with prompt-processor and then token generator for subsequent iterations.
Model | Device | Chipset | Target Runtime | Response Rate (tokens per second) | Time To First Token (range, seconds) | Tiny MMLU |
---|---|---|---|---|---|---|
Mistral-7B-Instruct-v0_3 | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | QNN | 10.73 | 0.18 - 5.79 | 58.85% |
Deploying Mistral 7B Instruct v3.0 on-device
Please follow this tutorial to compile QNN binaries and generate bundle assets to run ChatApp on Windows and on Android powered by QNN-Genie.
License
- The license for the original implementation of Mistral-7B-Instruct-v0_3 can be found here.
- The license for the compiled assets for on-device deployment can be found here
References
Community
- Join our AI Hub Slack community to collaborate, post questions and learn more about on-device AI.
- For questions or feedback please reach out to us.
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
Inference API (serverless) does not yet support pytorch models for this pipeline type.