v0.45.0

See https://github.com/quic/ai-hub-models/releases/v0.45.0 for changelog.

README.md

@@ -32,20 +32,7 @@ This model is an implementation of Qwen2-7B-Instruct found [here](https://github
   - 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: 5.16 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: 5.16 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.
-  - Minimum QNN SDK version required: 2.27.7
   - Supported languages: English, Chinese, German, French, Spanish, Portuguese, Italian, Dutch, Russian, Czech, Polish, Arabic, Persian, Hebrew, Turkish, Japanese, Korean, Vietnamese, Thai, Indonesian, Malay, Lao, Burmese, Cebuano, Khmer, Tagalog, Hindi, Bengali, Urdu.
   - 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.