metadata

library_name: pytorch
license: apache-2.0
pipeline_tag: text-generation
tags:
  - llm
  - generative_ai
  - quantized
  - android

Baichuan2-7B: Optimized for Mobile Deployment

State-of-the-art large language model useful on a variety of language understanding and generation tasks

Baichuan2-7B is a family of LLMs. It achieves the state-of-the-art performance of its size on standard Chinese and English authoritative benchmarks (C-EVAL/MMLU). 4-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 Baichuan2-PromptProcessor-Quantized's latency and average time per addition token is Baichuan2-TokenGenerator-Quantized's latency.

This model is an implementation of Baichuan2-7B found here.

More details on model performance accross various devices, can be found here.

Model Details

Model Type: Text generation
Model Stats:
- Input sequence length for Prompt Processor: 128
- Context length: 4096
- Number of parameters: 7.07B
- Precision: w4a16 + w8a16 (few layers)
- Num of key-value heads: 8
- Information about the model parts: Prompt Processor and Token Generator are split into 5 parts each. Each corresponding Prompt Processor and Token Generator part share weights.
- Prompt processor model size: 5.06 GB
- Prompt processor input (part1): 128 tokens
- Prompt processor output (part1): Embeddings output
- Prompt processor input (other parts): 128 tokens + KVCache initialized with pad token
- Prompt processor output (other parts): 128 output tokens + KVCache for token generator
- Token generator model size: 5.06 GB
- Token generator input (part1): 128 tokens
- Token generator output (part1): Embeddings output
- Token generator input (other parts): 1 input token + past KVCache
- Token generator output (other parts): 1 output token + KVCache for next iteration
- Use: Initiate conversation with prompt-processor and then token generator for subsequent iterations.
- Supported languages: Chinese and English.
- Minimum QNN SDK version required: 2.27.7
- 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	Device	Chipset	Target Runtime	Response Rate (tokens per second)	Time To First Token (range, seconds)
Baichuan2-7B	Snapdragon 8 Elite QRD	Snapdragon® 8 Elite	QNN	7.72	0.20804799999999998 - 6.6575359999999995

Deploying Baichuan2-7B on-device

Please follow the LLM on-device deployment tutorial.

License

The license for the original implementation of Baichuan2-7B 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