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Llama-v2-7B-Chat

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

Llama 2 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‑KVCache‑Quantized's latency.

Technical Details

Input sequence length for Prompt Processor:1024
Context length:1024
Number of parameters:7B
Precision:w4a16 + w8a16 (few layers)
Model-1 (Prompt Processor):Llama-PromptProcessor-Quantized
Prompt processor model size:3.6 GB
Prompt processor input:1024 tokens
Prompt processor output:1024 output tokens + KVCache for token generator
Model-2 (Token Generator):Llama-TokenGenerator-KVCache-Quantized
Token generator model size:3.6 GB
Token generator input:1 input token + past KVCache
Token generator output:1 output token + KVCache for next iteration
Use:Initiate conversation with prompt-processor and then token generator for subsequent iterations.
Minimum QNN SDK version required:2.27.0
Supported languages:English.
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. For Llama-v2-7B-Chat, both values in the range are the same since prompt length is the full context length (1024 tokens).
Response Rate:Rate of response generation after the first response token.

Applicable Scenarios

  • Dialogue
  • Content Generation
  • Customer Support

Licenses

Source Model:LLAMA2
Deployable Model:LLAMA2

Tags

  • llm
  • generative-ai
  • quantized

Supported Compute Devices

  • Snapdragon X Elite CRD

Supported Compute Chipsets

  • Snapdragon® X Elite

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