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--- |
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library_name: pytorch |
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license: llama3 |
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pipeline_tag: text-generation |
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tags: |
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- llm |
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- generative_ai |
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- quantized |
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- android |
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--- |
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![](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/llama_v3_8b_chat_quantized/web-assets/model_demo.png) |
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# Llama-v3-8B-Chat: Optimized for Mobile Deployment |
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## State-of-the-art large language model useful on a variety of language understanding and generation tasks |
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Llama 3 is a family of LLMs. The "Chat" at the end indicates that the model is optimized for chatbot-like dialogue. The model is quantized to w4a16 (4-bit weights and 16-bit activations) and part of the model is quantized to w8a16 (8-bit weights and 16-bit activations) making it suitable for on-device deployment. For Prompt and output length specified below, the time to first token is Llama-PromptProcessor-Quantized's latency and average time per addition token is Llama-TokenGenerator-Quantized's latency. |
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This is based on the implementation of Llama-v3-8B-Chat found |
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[here]({source_repo}). More details on model performance |
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accross various devices, can be found [here](https://aihub.qualcomm.com/models/llama_v3_8b_chat_quantized). |
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### Model Details |
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- **Model Type:** Text generation |
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- **Model Stats:** |
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- Context length: 4096 |
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- Number of parameters: 8B |
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- Model size: 4.8GB |
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- Precision: w4a16 + w8a16 (few layers) |
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- Num of key-value heads: 8 |
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- Model-1 (Prompt Processor): Llama-PromptProcessor-Quantized |
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- Prompt processor input: 128 tokens + position embeddings + attention mask + KV cache inputs |
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- Prompt processor output: 128 output tokens + KV cache outputs |
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- Model-2 (Token Generator): Llama-TokenGenerator-Quantized |
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- Token generator input: 1 input token + position embeddings + attention mask + KV cache inputs |
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- Token generator output: 1 output token + KV cache outputs |
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- Use: Initiate conversation with prompt-processor and then token generator for subsequent iterations. |
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| Model | Device | Chipset | Target Runtime | Response Rate (Tokens/Second) | Time To First Token (TTFT) Range (Seconds) | Evaluation | |
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|---|---|---|---|---|---|---| |
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| Llama-v3-8B-Chat | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | QNN | 66.14 | (0.028, 0.92) | -- | -- | |
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| Llama-v3-8B-Chat | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | QNN | 66.14 | (0.028, 0.92) | -- | -- | |
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| Llama-v3-8B-Chat | Samsung Galaxy S23 Ultra | Snapdragon® 8 Gen 2 | QNN | 66.14 | (0.028, 0.92) | -- | -- | |
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| Llama-v3-8B-Chat | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN | 66.14 | (0.028, 0.92) | -- | -- | |
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| Llama-v3-8B-Chat | QCS8550 (Proxy) | QCS8550 Proxy | QNN | 66.14 | (0.028, 0.92) | -- | -- | |
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## Deploying Llama 3 on-device |
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Please follow [this tutorial](https://github.com/quic/ai-hub-apps/tree/main/tutorials/llama) |
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to compile QNN binaries and generate bundle assets to run [ChatApp on Windows](https://github.com/quic/ai-hub-apps/tree/main/apps/windows/cpp/ChatApp) and on Android powered by QNN-Genie. |
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## Sample output prompts generated on-device |
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1. --prompt "where is California?" |
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``` |
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------- Response Summary -------- |
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Prompt: where is California? |
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Response: California is a state located on the West Coast of |
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``` |
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2. --prompt "what is 2+3?" --max-output-tokens 30 |
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``` |
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-------- Response Summary -------- |
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Prompt: what is 2+3? |
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Response: 2 + 3 = 5 |
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``` |
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3. --prompt "what is superposition in Quantum Physics?" --max-output-tokens 30 |
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``` |
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Prompt: what is superposition in Quantum Physics? |
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Response: Superposition is a fundamental concept in quantum mechanics, which is a branch of physics that studies the behavior of matter and energy at a very |
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``` |
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## License |
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* The license for the original implementation of Llama-v3-8B-Chat can be found [here](https://github.com/facebookresearch/llama/blob/main/LICENSE). |
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* The license for the compiled assets for on-device deployment can be found [here](https://github.com/facebookresearch/llama/blob/main/LICENSE) |
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## References |
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* [LLaMA: Open and Efficient Foundation Language Models](https://ai.meta.com/blog/meta-llama-3/) |
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* [Source Model Implementation](https://github.com/meta-llama/llama3/tree/main) |
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## Community |
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* 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. |
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* For questions or feedback please [reach out to us](mailto:[email protected]). |
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## Usage and Limitations |
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Model may not be used for or in connection with any of the following applications: |
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- Accessing essential private and public services and benefits; |
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- Administration of justice and democratic processes; |
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- Assessing or recognizing the emotional state of a person; |
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- Biometric and biometrics-based systems, including categorization of persons based on sensitive characteristics; |
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- Education and vocational training; |
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- Employment and workers management; |
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- Exploitation of the vulnerabilities of persons resulting in harmful behavior; |
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- General purpose social scoring; |
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- Law enforcement; |
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- Management and operation of critical infrastructure; |
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- Migration, asylum and border control management; |
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- Predictive policing; |
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- Real-time remote biometric identification in public spaces; |
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- Recommender systems of social media platforms; |
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- Scraping of facial images (from the internet or otherwise); and/or |
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- Subliminal manipulation |
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