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Model: TIGER-Lab/Mantis-8B-siglip-llama3 Source: Original Platform
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README.md
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---
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base_model: TIGER-Lab/Mantis-8B-siglip-llama3-pretraind
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tags:
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- multimodal
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- lmm
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- vlm
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- llava
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- siglip
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- llama3
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- mantis
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model-index:
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- name: Mantis-8B-siglip-llama3
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results: []
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license: llama3
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datasets:
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- TIGER-Lab/Mantis-Instruct
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language:
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- en
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---
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# 🔥 Mantis (TMLR 2024)
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[Paper](https://arxiv.org/abs/2405.01483) |
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[Website](https://tiger-ai-lab.github.io/Mantis/) |
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[Github](https://github.com/TIGER-AI-Lab/Mantis) |
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[Models](https://huggingface.co/collections/TIGER-Lab/mantis-6619b0834594c878cdb1d6e4) |
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[Demo](https://huggingface.co/spaces/TIGER-Lab/Mantis) |
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[Wandb](https://api.wandb.ai/links/dongfu/iydlrqgj)
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## Summary
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- Mantis is an LLaMA-3 based LMM with **interleaved text and image as inputs**, train on Mantis-Instruct under academic-level resources (i.e. 36 hours on 16xA100-40G).
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- Mantis is trained to have multi-image skills including co-reference, reasoning, comparing, temporal understanding.
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- Mantis reaches the state-of-the-art performance on five multi-image benchmarks (NLVR2, Q-Bench, BLINK, MVBench, Mantis-Eval), and also maintain a strong single-image performance on par with CogVLM and Emu2.
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## Multi-Image Performance
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| Models | Size | Format | NLVR2 | Q-Bench | Mantis-Eval | BLINK | MVBench | Avg |
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|--------------------|:----:|:--------:|:-----:|:-------:|:-----------:|:-----:|:-------:|:----:|
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| GPT-4V | - | sequence | 88.80 | 76.52 | 62.67 | 51.14 | 43.50 | 64.5 |
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| Open Source Models | | | | | | | | |
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| Random | - | - | 48.93 | 40.20 | 23.04 | 38.09 | 27.30 | 35.5 |
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| Kosmos2 | 1.6B | merge | 49.00 | 35.10 | 30.41 | 37.50 | 21.62 | 34.7 |
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| LLaVA-v1.5 | 7B | merge | 53.88 | 49.32 | 31.34 | 37.13 | 36.00 | 41.5 |
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| LLava-V1.6 | 7B | merge | 58.88 | 54.80 | 45.62 | 39.55 | 40.90 | 48.0 |
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| Qwen-VL-Chat | 7B | merge | 58.72 | 45.90 | 39.17 | 31.17 | 42.15 | 43.4 |
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| Fuyu | 8B | merge | 51.10 | 49.15 | 27.19 | 36.59 | 30.20 | 38.8 |
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| BLIP-2 | 13B | merge | 59.42 | 51.20 | 49.77 | 39.45 | 31.40 | 46.2 |
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| InstructBLIP | 13B | merge | 60.26 | 44.30 | 45.62 | 42.24 | 32.50 | 45.0 |
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| CogVLM | 17B | merge | 58.58 | 53.20 | 45.16 | 41.54 | 37.30 | 47.2 |
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| OpenFlamingo | 9B | sequence | 36.41 | 19.60 | 12.44 | 39.18 | 7.90 | 23.1 |
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| Otter-Image | 9B | sequence | 49.15 | 17.50 | 14.29 | 36.26 | 15.30 | 26.5 |
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| Idefics1 | 9B | sequence | 54.63 | 30.60 | 28.11 | 24.69 | 26.42 | 32.9 |
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| VideoLLaVA | 7B | sequence | 56.48 | 45.70 | 35.94 | 38.92 | 44.30 | 44.3 |
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| Emu2-Chat | 37B | sequence | 58.16 | 50.05 | 37.79 | 36.20 | 39.72 | 44.4 |
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| Vila | 8B | sequence | 76.45 | 45.70 | 51.15 | 39.30 | 49.40 | 52.4 |
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| Idefics2 | 8B | sequence | 86.87 | 57.00 | 48.85 | 45.18 | 29.68 | 53.5 |
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| Mantis-CLIP | 8B | sequence | 84.66 | 66.00 | 55.76 | 47.06 | 48.30 | 60.4 |
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| Mantis-SIGLIP | 8B | sequence | 87.43 | 69.90 | **59.45** | 46.35 | 50.15 | 62.7 |
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| Mantis-Flamingo | 9B | sequence | 52.96 | 46.80 | 32.72 | 38.00 | 40.83 | 42.3 |
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| Mantis-Idefics2 | 8B | sequence | **89.71** | **75.20** | 57.14 | **49.05** | **51.38** | **64.5** |
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| $\Delta$ over SOTA | - | - | +2.84 | +18.20 | +8.30 | +3.87 | +1.98 | +11.0 |
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## Single-Image Performance
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| Model | Size | TextVQA | VQA | MMB | MMMU | OKVQA | SQA | MathVista | Avg |
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|-----------------|:----:|:-------:|:----:|:----:|:----:|:-----:|:----:|:---------:|:----:|
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| OpenFlamingo | 9B | 46.3 | 58.0 | 32.4 | 28.7 | 51.4 | 45.7 | 18.6 | 40.2 |
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| Idefics1 | 9B | 39.3 | 68.8 | 45.3 | 32.5 | 50.4 | 51.6 | 21.1 | 44.1 |
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| InstructBLIP | 7B | 33.6 | 75.2 | 38.3 | 30.6 | 45.2 | 70.6 | 24.4 | 45.4 |
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| Yi-VL | 6B | 44.8 | 72.5 | 68.4 | 39.1 | 51.3 | 71.7 | 29.7 | 53.9 |
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| Qwen-VL-Chat | 7B | 63.8 | 78.2 | 61.8 | 35.9 | 56.6 | 68.2 | 15.5 | 54.3 |
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| LLaVA-1.5 | 7B | 58.2 | 76.6 | 64.8 | 35.3 | 53.4 | 70.4 | 25.6 | 54.9 |
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| Emu2-Chat | 37B | <u>66.6</u> | **84.9** | 63.6 | 36.3 | **64.8** | 65.3 | 30.7 | 58.9 |
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| CogVLM | 17B | **70.4** | <u>82.3</u> | 65.8 | 32.1 | <u>64.8</u> | 65.6 | 35.0 | 59.4 |
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| Idefics2 | 8B | 70.4 | 79.1 | <u>75.7</u> | **43.0** | 53.5 | **86.5** | **51.4** | **65.7** |
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| Mantis-CLIP | 8B | 56.4 | 73.0 | 66.0 | 38.1 | 53.0 | 73.8 | 31.7 | 56.0 |
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| Mantis-SigLIP | 8B | 59.2 | 74.9 | 68.7 | 40.1 | 55.4 | 74.9 | 34.4 | 58.2 |
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| Mantis-Idefics2 | 8B | 63.5 | 77.6 | 75.7 | <u>41.1</u> | 52.6 | <u>81.3</u> | <u>40.4</u> | <u>61.7</u> |
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## How to use
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### Installation
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```bash
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# This only installs minimum packages (torch, transformers, accelerate) for inference, no redundant packages are installed.
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pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
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```
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### Run example inference:
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```python
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from mantis.models.mllava import chat_mllava
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from PIL import Image
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import torch
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image1 = "image1.jpg"
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image2 = "image2.jpg"
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images = [Image.open(image1), Image.open(image2)]
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# load processor and model
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from mantis.models.mllava import MLlavaProcessor, LlavaForConditionalGeneration
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processor = MLlavaProcessor.from_pretrained("TIGER-Lab/Mantis-8B-siglip-llama3")
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attn_implementation = None # or "flash_attention_2"
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model = LlavaForConditionalGeneration.from_pretrained("TIGER-Lab/Mantis-8B-siglip-llama3", device_map="cuda", torch_dtype=torch.bfloat16, attn_implementation=attn_implementation)
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generation_kwargs = {
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"max_new_tokens": 1024,
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"num_beams": 1,
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"do_sample": False
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}
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# chat
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text = "Describe the difference of <image> and <image> as much as you can."
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response, history = chat_mllava(text, images, model, processor, **generation_kwargs)
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print("USER: ", text)
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print("ASSISTANT: ", response)
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text = "How many wallets are there in image 1 and image 2 respectively?"
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response, history = chat_mllava(text, images, model, processor, history=history, **generation_kwargs)
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print("USER: ", text)
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print("ASSISTANT: ", response)
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"""
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USER: Describe the difference of <image> and <image> as much as you can.
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ASSISTANT: The second image has more variety in terms of colors and designs. While the first image only shows two brown leather pouches, the second image features four different pouches in various colors and designs, including a purple one with a gold coin, a red one with a gold coin, a black one with a gold coin, and a brown one with a gold coin. This variety makes the second image more visually interesting and dynamic.
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USER: How many wallets are there in image 1 and image 2 respectively?
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ASSISTANT: There are two wallets in image 1, and four wallets in image 2.
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"""
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```
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### Training
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See [mantis/train](https://github.com/TIGER-AI-Lab/Mantis/tree/main/mantis/train) for details
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### Evaluation
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See [mantis/benchmark](https://github.com/TIGER-AI-Lab/Mantis/tree/main/mantis/benchmark) for details
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**Please cite our paper or give a star to out Github repo if you find this model useful**
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## Citation
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```
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@article{Jiang2024MANTISIM,
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title={MANTIS: Interleaved Multi-Image Instruction Tuning},
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author={Dongfu Jiang and Xuan He and Huaye Zeng and Cong Wei and Max W.F. Ku and Qian Liu and Wenhu Chen},
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journal={Transactions on Machine Learning Research},
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year={2024},
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volume={2024},
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url={https://openreview.net/forum?id=skLtdUVaJa}
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}
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```
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"LlavaForConditionalGeneration"
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"projector_hidden_act": "gelu",
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"text_config": {
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"_name_or_path": "meta-llama/Meta-Llama-3-8B-Instruct",
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"LlamaForCausalLM"
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"model_type": "llama",
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-05,
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"rope_theta": 500000.0,
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"torch_dtype": "bfloat16",
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"vocab_size": 128258
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"torch_dtype": "bfloat16",
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"image_size": 384,
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"intermediate_size": 4304,
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"layer_norm_eps": 1e-06,
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"model_type": "siglip_vision_model",
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"num_attention_heads": 16,
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"num_hidden_layers": 27,
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"patch_size": 14
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"vision_feature_select_strategy": "default",
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"vision_tower.vision_model.encoder.layers.9.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
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"vision_tower.vision_model.encoder.layers.9.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
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|
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"vision_tower.vision_model.head.attention.in_proj_bias": "model-00001-of-00004.safetensors",
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"vision_tower.vision_model.head.attention.in_proj_weight": "model-00001-of-00004.safetensors",
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"vision_tower.vision_model.head.attention.out_proj.weight": "model-00001-of-00004.safetensors",
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"vision_tower.vision_model.head.layernorm.bias": "model-00001-of-00004.safetensors",
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"vision_tower.vision_model.head.layernorm.weight": "model-00001-of-00004.safetensors",
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"vision_tower.vision_model.head.mlp.fc1.bias": "model-00001-of-00004.safetensors",
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"vision_tower.vision_model.head.mlp.fc1.weight": "model-00001-of-00004.safetensors",
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"vision_tower.vision_model.head.mlp.fc2.bias": "model-00001-of-00004.safetensors",
|
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"vision_tower.vision_model.head.mlp.fc2.weight": "model-00001-of-00004.safetensors",
|
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"vision_tower.vision_model.head.probe": "model-00001-of-00004.safetensors",
|
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"vision_tower.vision_model.post_layernorm.bias": "model-00001-of-00004.safetensors",
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"vision_tower.vision_model.post_layernorm.weight": "model-00001-of-00004.safetensors"
|
||||
}
|
||||
}
|
||||
37
preprocessor_config.json
Normal file
37
preprocessor_config.json
Normal file
@@ -0,0 +1,37 @@
|
||||
{
|
||||
"_valid_processor_keys": [
|
||||
"images",
|
||||
"do_resize",
|
||||
"size",
|
||||
"resample",
|
||||
"do_rescale",
|
||||
"rescale_factor",
|
||||
"do_normalize",
|
||||
"image_mean",
|
||||
"image_std",
|
||||
"return_tensors",
|
||||
"data_format",
|
||||
"input_data_format"
|
||||
],
|
||||
"do_normalize": true,
|
||||
"do_rescale": true,
|
||||
"do_resize": true,
|
||||
"image_mean": [
|
||||
0.5,
|
||||
0.5,
|
||||
0.5
|
||||
],
|
||||
"image_processor_type": "SiglipImageProcessor",
|
||||
"image_std": [
|
||||
0.5,
|
||||
0.5,
|
||||
0.5
|
||||
],
|
||||
"processor_class": "MLlavaProcessor",
|
||||
"resample": 3,
|
||||
"rescale_factor": 0.00392156862745098,
|
||||
"size": {
|
||||
"height": 384,
|
||||
"width": 384
|
||||
}
|
||||
}
|
||||
21
special_tokens_map.json
Normal file
21
special_tokens_map.json
Normal file
@@ -0,0 +1,21 @@
|
||||
{
|
||||
"additional_special_tokens": [
|
||||
"<image>",
|
||||
"<|pad|>"
|
||||
],
|
||||
"bos_token": {
|
||||
"content": "<|begin_of_text|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "<|end_of_text|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"unk_token": "<unk>"
|
||||
}
|
||||
410578
tokenizer.json
Normal file
410578
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
2095
tokenizer_config.json
Normal file
2095
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
3
training_args.bin
Normal file
3
training_args.bin
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:24089c5ab7a2f2796b48c8aaf15f9207f76287e9c8c6cfe7ce31731e3fbb330c
|
||||
size 6392
|
||||
Reference in New Issue
Block a user