| --- |
| license: other |
| tags: |
| - heal |
| - horizon |
| --- |
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| # InternVL2-2B |
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| **Original model repository:** [OpenGVLab/InternVL2-2B](https://huggingface.co/OpenGVLab/InternVL2-2B) |
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| ## Model Introduction |
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| InternVL2-2B is an instruction-tuned Vision-Language Model (VLM) for image understanding and text generation. It combines an InternViT-300M vision encoder, an MLP projector, and InternLM2-Chat-1.8B as its language model. Typical applications include visual question answering, OCR, image description, document and chart understanding, and multimodal dialogue. |
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| ## Deployment Metrics |
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| ### Model Parameters |
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| | Metric | Value | |
| |---|---:| |
| | Total model parameters | 2.206B | |
| | Vision model (ViT) parameters | 316.6M | |
| | Language model (LM) parameters | 1.889B | |
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| Parameter counts are calculated from the tensors stored in the upstream checkpoint. |
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| ### Performance Metrics |
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| | Chips | Data Type | ViT Image Size | Sequence Length (tokens) | Maximum Context Length (tokens) | BPU Cores (ViT / Prefill / Decode) | ViT Latency (ms) | TTFT (ms) | Prefill TPS (token/s) | Decode TPS (token/s) | BPU Memory (GB) | CPU Memory (GB) | |
| |---|---|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:| |
| | J6P | W8A8 | 448 × 448 | 512 | 1024 | 4 / 4 / 4 | 41.535 | 84.448 | 13,265.273 | 70.473 | 2.4 | 0.79 | |
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| > **Note:** TTFT includes preprocessing and ViT latency. Memory values represent the peak memory usage measured during the specified performance test. |
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