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Model: remyxai/SpaceQwen2.5-VL-3B-Instruct Source: Original Platform
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LICENSE
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Qwen RESEARCH LICENSE AGREEMENT
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|
||||
Qwen RESEARCH LICENSE AGREEMENT Release Date: September 19, 2024
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By clicking to agree or by using or distributing any portion or element of the Qwen Materials, you will be deemed to have recognized and accepted the content of this Agreement, which is effective immediately.
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491
README.md
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README.md
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---
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||||
base_model:
|
||||
- Qwen/Qwen2.5-VL-3B-Instruct
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||||
datasets:
|
||||
- remyxai/OpenSpaces
|
||||
language:
|
||||
- en
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||||
library_name: transformers
|
||||
license_name: qwen-research
|
||||
license_link: https://huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct/blob/main/LICENSE
|
||||
pipeline_tag: image-text-to-text
|
||||
tags:
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||||
- remyx
|
||||
- vqasynth
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||||
- spatial-reasoning
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||||
- multimodal
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||||
- vlm
|
||||
- vision-language
|
||||
- robotics
|
||||
- distance-estimation
|
||||
- embodied-ai
|
||||
- quantitative-spatial-reasoning
|
||||
new_version: remyxai/SpaceThinker-Qwen2.5VL-3B
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||||
model-index:
|
||||
- name: SpaceQwen2.5-VL-3B-Instruct
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||||
results:
|
||||
- task:
|
||||
type: visual-question-answering
|
||||
name: Spatial Reasoning
|
||||
dataset:
|
||||
name: 3DSRBench
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||||
type: benchmark
|
||||
metrics:
|
||||
- type: success_rate
|
||||
name: Overall Success Rate
|
||||
value: 0.515
|
||||
results_by_subcategory:
|
||||
- name: 3D Positional Relation / Orientation
|
||||
success_rate: 0.4706
|
||||
- name: Object Localization / 3D Localization
|
||||
success_rate: 0.5629
|
||||
- name: Object Properties / Size
|
||||
success_rate: 0.5116
|
||||
- task:
|
||||
type: visual-question-answering
|
||||
name: Spatial Reasoning
|
||||
dataset:
|
||||
name: BLINK
|
||||
type: benchmark
|
||||
metrics:
|
||||
- type: success_rate
|
||||
name: Overall Success Rate
|
||||
value: 0.5
|
||||
results_by_subcategory:
|
||||
- name: 3D Positional Relation / Orientation
|
||||
success_rate: 0.6503
|
||||
- name: Counting / Object Counting
|
||||
success_rate: 0.6083
|
||||
- name: Depth and Distance / Relative
|
||||
success_rate: 0.5161
|
||||
- name: Object Localization / 2D Localization
|
||||
success_rate: 0.4426
|
||||
- name: Point and Object Tracking / Point Correspondence
|
||||
success_rate: 0.2849
|
||||
- task:
|
||||
type: visual-question-answering
|
||||
name: Spatial Reasoning
|
||||
dataset:
|
||||
name: MMIU
|
||||
type: benchmark
|
||||
metrics:
|
||||
- type: success_rate
|
||||
name: Overall Success Rate
|
||||
value: 0.3045
|
||||
results_by_subcategory:
|
||||
- name: Camera and Image Transformation / 2D Transformation
|
||||
success_rate: 0.245
|
||||
- name: Camera and Image Transformation / 3D Camera Pose
|
||||
success_rate: 0.215
|
||||
- name: Camera and Image Transformation / Camera Motion
|
||||
success_rate: 0.4436
|
||||
- name: Depth and Distance / Absolute
|
||||
success_rate: 0.265
|
||||
- name: Object Localization / 3D Localization
|
||||
success_rate: 0.48
|
||||
- name: Point and Object Tracking / 3D Tracking
|
||||
success_rate: 0.24
|
||||
- name: Point and Object Tracking / Point Correspondence
|
||||
success_rate: 0.28
|
||||
- task:
|
||||
type: visual-question-answering
|
||||
name: Spatial Reasoning
|
||||
dataset:
|
||||
name: MMVP
|
||||
type: benchmark
|
||||
metrics:
|
||||
- type: success_rate
|
||||
name: Overall Success Rate
|
||||
value: 0.5767
|
||||
results_by_subcategory:
|
||||
- name: Others / Miscellaneous
|
||||
success_rate: 0.5767
|
||||
- task:
|
||||
type: visual-question-answering
|
||||
name: Spatial Reasoning
|
||||
dataset:
|
||||
name: QSpatialBench-Plus
|
||||
type: benchmark
|
||||
metrics:
|
||||
- type: success_rate
|
||||
name: Overall Success Rate
|
||||
value: 0.3663
|
||||
results_by_subcategory:
|
||||
- name: Depth and Distance / Absolute
|
||||
success_rate: 0.3663
|
||||
- task:
|
||||
type: visual-question-answering
|
||||
name: Spatial Reasoning
|
||||
dataset:
|
||||
name: QSpatialBench-ScanNet
|
||||
type: benchmark
|
||||
metrics:
|
||||
- type: success_rate
|
||||
name: Overall Success Rate
|
||||
value: 0.33
|
||||
results_by_subcategory:
|
||||
- name: Depth and Distance / Absolute
|
||||
success_rate: 0.216
|
||||
- name: Object Properties / Size
|
||||
success_rate: 0.4444
|
||||
- task:
|
||||
type: visual-question-answering
|
||||
name: Spatial Reasoning
|
||||
dataset:
|
||||
name: RealWorldQA
|
||||
type: benchmark
|
||||
metrics:
|
||||
- type: success_rate
|
||||
name: Overall Success Rate
|
||||
value: 0.4392
|
||||
results_by_subcategory:
|
||||
- name: Others / Miscellaneous
|
||||
success_rate: 0.4392
|
||||
- task:
|
||||
type: visual-question-answering
|
||||
name: Spatial Reasoning
|
||||
dataset:
|
||||
name: SpatialSense
|
||||
type: benchmark
|
||||
metrics:
|
||||
- type: success_rate
|
||||
name: Overall Success Rate
|
||||
value: 0.6554
|
||||
results_by_subcategory:
|
||||
- name: 3D Positional Relation / Orientation
|
||||
success_rate: 0.6554
|
||||
- task:
|
||||
type: visual-question-answering
|
||||
name: Spatial Reasoning
|
||||
dataset:
|
||||
name: VGBench
|
||||
type: benchmark
|
||||
metrics:
|
||||
- type: success_rate
|
||||
name: Overall Success Rate
|
||||
value: 0.2615
|
||||
results_by_subcategory:
|
||||
- name: Camera and Image Transformation / 2D Transformation
|
||||
success_rate: 0.2277
|
||||
- name: Camera and Image Transformation / 3D Camera Pose
|
||||
success_rate: 0.2438
|
||||
- name: Depth and Distance / Absolute
|
||||
success_rate: 0.2696
|
||||
- name: Depth and Distance / Relative
|
||||
success_rate: 0.1945
|
||||
- name: Object Localization / 3D Localization
|
||||
success_rate: 0.3733
|
||||
- name: Point and Object Tracking / 3D Tracking
|
||||
success_rate: 0.2655
|
||||
- task:
|
||||
type: visual-question-answering
|
||||
name: Spatial Reasoning
|
||||
dataset:
|
||||
name: VSI-Bench_8
|
||||
type: benchmark
|
||||
metrics:
|
||||
- type: success_rate
|
||||
name: Overall Success Rate
|
||||
value: 0.2322
|
||||
results_by_subcategory:
|
||||
- name: 3D Positional Relation / Orientation
|
||||
success_rate: 0.3843
|
||||
- name: Counting / Object Counting
|
||||
success_rate: 0.1715
|
||||
- name: Depth and Distance / Absolute
|
||||
success_rate: 0.0299
|
||||
- name: Depth and Distance / Relative
|
||||
success_rate: 0.3521
|
||||
- name: Object Properties / Size
|
||||
success_rate: 0.2323
|
||||
- name: Others / Miscellaneous
|
||||
success_rate: 0.2525
|
||||
- task:
|
||||
type: visual-question-answering
|
||||
name: Spatial Reasoning
|
||||
dataset:
|
||||
name: VSR-ZeroShot
|
||||
type: benchmark
|
||||
metrics:
|
||||
- type: success_rate
|
||||
name: Overall Success Rate
|
||||
value: 0.7373
|
||||
results_by_subcategory:
|
||||
- name: 3D Positional Relation / Orientation
|
||||
success_rate: 0.7373
|
||||
- task:
|
||||
type: visual-question-answering
|
||||
name: Spatial Reasoning
|
||||
dataset:
|
||||
name: cvbench
|
||||
type: benchmark
|
||||
metrics:
|
||||
- type: success_rate
|
||||
name: Overall Success Rate
|
||||
value: 0.5179
|
||||
results_by_subcategory:
|
||||
- name: Counting / Object Counting
|
||||
success_rate: 0.6168
|
||||
- name: Depth and Distance / Relative
|
||||
success_rate: 0.4925
|
||||
- name: Object Localization / 3D Localization
|
||||
success_rate: 0.4446
|
||||
- task:
|
||||
type: visual-question-answering
|
||||
name: Spatial Reasoning
|
||||
dataset:
|
||||
name: spatialbench
|
||||
type: benchmark
|
||||
metrics:
|
||||
- type: success_rate
|
||||
name: Overall Success Rate
|
||||
value: 0.4879
|
||||
results_by_subcategory:
|
||||
- name: 3D Positional Relation / Orientation
|
||||
success_rate: 0.5294
|
||||
- name: Counting / Object Counting
|
||||
success_rate: 0.7
|
||||
- name: Object Properties / Existence
|
||||
success_rate: 0.45
|
||||
- name: Object Properties / Reachability
|
||||
success_rate: 0.5
|
||||
- name: Object Properties / Size
|
||||
success_rate: 0.25
|
||||
---
|
||||
|
||||
<img src="https://cdn-uploads.huggingface.co/production/uploads/647777304ae93470ffc28913/v4edJliSy46xBA8g5ZXf8.png" width="500"/>
|
||||
|
||||
# SpaceQwen2.5-VL-3B-Instruct
|
||||
|
||||
The model was presented in the paper [OmniSpatial: Towards Comprehensive Spatial Reasoning Benchmark for Vision Language Models](https://huggingface.co/papers/2506.03135). More information can be found at the [project page](https://qizekun.github.io/omnispatial/).
|
||||
|
||||
|
||||
- **Model Type:** Multimodal, Vision-Language Model
|
||||
- **Architecture**: `Qwen2.5-VL-3B-Instruct`
|
||||
- **Model Size:** 3.75B parameters (FP16)
|
||||
- **Finetuned from:** Qwen/Qwen2.5-VL-3B-Instruct
|
||||
- **Finetune Strategy:** LoRA (Low-Rank Adaptation)
|
||||
- **License:** Apache-2.0
|
||||
|
||||
### Model Overview
|
||||
|
||||
This model uses data synthesis techniques and publicly available models to reproduce the work described in SpatialVLM to enhance the spatial reasoning of multimodal models.
|
||||
With a pipeline of expert models, we can infer spatial relationships between objects in a scene to create a VQA dataset for spatial reasoning.
|
||||
|
||||
|
||||
## Running SpaceQwen2.5-VL-3B-Instruct
|
||||
|
||||
### Ollama
|
||||
To launch with ollama, run:
|
||||
```bash
|
||||
ollama run hf.co/remyxai/SpaceQwen2.5-VL-3B-Instruct:latest
|
||||
```
|
||||
|
||||
### Transformers
|
||||
|
||||
Install qwen dependencies:
|
||||
```
|
||||
pip install qwen-vl-utils[decord]==0.0.8
|
||||
```
|
||||
|
||||
To run inference on a sample image:
|
||||
```python
|
||||
from transformers import Qwen2_5_VLForConditionalGeneration, AutoTokenizer, AutoProcessor
|
||||
from qwen_vl_utils import process_vision_info
|
||||
|
||||
model = Qwen2_5_VLForConditionalGeneration.from_pretrained(
|
||||
"remyxai/SpaceQwen2.5-VL-3B-Instruct", torch_dtype="auto", device_map="auto"
|
||||
)
|
||||
processor = AutoProcessor.from_pretrained("remyxai/SpaceQwen2.5-VL-3B-Instruct")
|
||||
|
||||
messages = [
|
||||
{
|
||||
"role": "user",
|
||||
"content": [
|
||||
{
|
||||
"type": "image",
|
||||
"image": "https://raw.githubusercontent.com/remyxai/VQASynth/refs/heads/main/assets/warehouse_sample_2.jpeg",
|
||||
},
|
||||
{"type": "text", "text": "What is the height of the man in the red hat in feet?"},
|
||||
],
|
||||
}
|
||||
]
|
||||
|
||||
# Preparation for inference
|
||||
text = processor.apply_chat_template(
|
||||
messages, tokenize=False, add_generation_prompt=True
|
||||
)
|
||||
image_inputs, video_inputs = process_vision_info(messages)
|
||||
inputs = processor(
|
||||
text=[text],
|
||||
images=image_inputs,
|
||||
videos=video_inputs,
|
||||
padding=True,
|
||||
return_tensors="pt",
|
||||
)
|
||||
inputs = inputs.to("cuda")
|
||||
|
||||
# Inference: Generation of the output
|
||||
generated_ids = model.generate(**inputs, max_new_tokens=128)
|
||||
generated_ids_trimmed = [
|
||||
out_ids[len(in_ids) :] for in_ids, out_ids in zip(inputs.input_ids, generated_ids)
|
||||
]
|
||||
output_text = processor.batch_decode(
|
||||
generated_ids_trimmed, skip_special_tokens=True, clean_up_tokenization_spaces=False
|
||||
)
|
||||
print(output_text)
|
||||
```
|
||||
|
||||
### GGUF
|
||||
|
||||
Or run **SpaceQwen2.5-VL-3B-Instruct** using **llama.cpp**:
|
||||
```bash
|
||||
./llama-qwen2vl-cli -m /path/to/SpaceQwen2.5-VL-3B-Instruct/SpaceQwen2.5-VL-3B-Instruct-F16.gguf \
|
||||
--mmproj /path/to/SpaceQwen2.5-VL-3B-Instruct/spaceqwen2.5-vl-3b-instruct-vision.gguf \
|
||||
-p "What's the height of the man in the red hat?" \
|
||||
--image /path/to/warehouse_sample_2.jpeg --threads 24 -ngl 99
|
||||
```
|
||||
|
||||
|
||||
## Dataset & Training
|
||||
|
||||
**SpaceQwen2.5-VL-3B-Instruct** uses LoRA to fine-tune [Qwen2.5-VL-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct) on the
|
||||
[OpenSpaces](https://huggingface.co/datasets/salma-remyx/OpenSpaces) dataset.
|
||||
|
||||
**Dataset Summary**:
|
||||
- ~10k synthetic spatial reasoning traces
|
||||
- Question types: spatial relations (distances (units), above, left-of, contains, closest to)
|
||||
- Format: image (RGB) + question + answer
|
||||
|
||||
- **Dataset:** [OpenSpaces](https://huggingface.co/datasets/remyxai/OpenSpaces)
|
||||
- **Code:** [VQASynth](https://github.com/remyxai/VQASynth/tree/main)
|
||||
- **Reference:** [SpatialVLM](https://spatial-vlm.github.io/)
|
||||
|
||||
Scripts for LoRA SFT available at [trl](https://github.com/huggingface/trl/blob/main/examples/scripts/sft_vlm.py)
|
||||
|
||||
|
||||
## Model Evaluation
|
||||
|
||||
### SpatialScore
|
||||
**SpaceQwen** shines in the 3D positional relations categories of the SpatialScore-Hard comparison featured in the table below:
|
||||
|
||||
|
||||
|
||||
Read more about the comprehensive spatial reasoning benchmark: [SpatialScore](https://haoningwu3639.github.io/SpatialScore/).
|
||||
|
||||
The following chart compares performance between **SpaceQwen** and **SpaceThinker** on the **SpatialScore** benchmarks sources.
|
||||
|
||||
<img src="https://cdn-uploads.huggingface.co/production/uploads/647777304ae93470ffc28913/M9DMOXkhef7-LBzGNxykm.png" alt="SpaceQwen_v_SpaceThinker" style="max-height: 250px;">
|
||||
|
||||
### OmniSpatial
|
||||
|
||||
**OmniSpatial** is another comprehensive spatial reasoning benchmark that assesses dynamic reasoning, complex spatial logic, spatial interaction, and perspective-taking capabilities.
|
||||
|
||||
|
||||
Learn more about [OmniSpatial](https://qizekun.github.io/omnispatial/).
|
||||
|
||||
### SpaCE-10
|
||||
|
||||
|
||||
|
||||
| **Model** | **Overall** | **EQ** | **SQ** | **SA** | **OO** | **OS** | **EP** | **FR** | **SP** | **Source** |
|
||||
|--------------------------|-------------|----------|----------|----------|----------|----------|----------|----------|----------|-------------|
|
||||
| InternVL2.5-4B | **36.01** | **34.30**| 34.40 | 43.60 | 44.40 | 16.50 | **31.10**| **50.10**| **33.70**| Table |
|
||||
| SpaceThinker | 32.72 | 32.73 | 24.81 | 47.26 | 50.33 | 33.63 | 9.25 | 37.54 | 26.25 | GPT Eval |
|
||||
| SpaceOm | 32.32 | 32.47 | 24.81 | **47.63**| 50.00 | 32.52 | 9.12 | 37.04 | 25.00 | GPT Eval |
|
||||
| **SpaceQwen** | 31.98 | 31.19 | 25.89 | 41.61 | **51.98**| **35.18**| 10.97 | 36.54 | 22.50 | GPT Eval |
|
||||
| Qwen2.5-VL-3B-Instruct | 30.00 | 31.70 | **45.50**| 39.00 | 43.00 | 25.30 | 11.50 | 22.80 | 21.20 | Table |
|
||||
|
||||
|
||||
**Legend:**
|
||||
- EQ: Entity Quantification
|
||||
- SQ: Scene Quantification
|
||||
- SA: Size Assessment
|
||||
- OO: Object-Object spatial relations
|
||||
- OS: Object-Scene spatial relations
|
||||
- EP: Entity Presence
|
||||
- FR: Functional Reasoning
|
||||
- SP: Spatial Planning
|
||||
|
||||
> ℹ️ Note: Scores for SpaceQwen, SpaceThinker, SpaceOm are generated via `gpt_eval_score` on single-choice (`*-single`) versions of the SpaCE-10 benchmark tasks. Other entries reflect leaderboard accuracy scores from the official SpaCE-10 evaluation table.
|
||||
|
||||
Read more about the [SpaCE-10 benchmark](https://arxiv.org/pdf/2506.07966v1) or see [results here](https://huggingface.co/datasets/salma-remyx/SpaceQwen_SpaCE-10_Results/blob/main/20250612_013312_results.json)
|
||||
|
||||
|
||||
### SIRI-Bench
|
||||
|
||||
[SIRI-Bench](https://arxiv.org/pdf/2506.14512v1) is a video-based benchmark designed to evaluate complex spatial reasoning capabilities
|
||||
|
||||
|
||||
|
||||
|
||||
### MindCube
|
||||
|
||||
[MindCube](https://huggingface.co/datasets/MLL-Lab/MindCube) is a benchmark for assessing [Spatial Mental Modeling from Limited Views](https://arxiv.org/pdf/2506.21458)
|
||||
|
||||
|
||||
|
||||
|
||||
## ⚠️ Limitations & Ethical Considerations
|
||||
|
||||
- Performance may degrade in cluttered environments or camera perspective.
|
||||
- This model was fine-tuned using synthetic reasoning over an internet image dataset.
|
||||
- Multimodal biases inherent to the base model (Qwen2.5-VL) may persist.
|
||||
- Not intended for use in safety-critical or legal decision-making.
|
||||
|
||||
> Users are encouraged to evaluate outputs critically and consider fine-tuning for domain-specific safety and performance.
|
||||
|
||||
## Citation
|
||||
```
|
||||
@article{chen2024spatialvlm,
|
||||
title = {SpatialVLM: Endowing Vision-Language Models with Spatial Reasoning Capabilities},
|
||||
author = {Chen, Boyuan and Xu, Zhuo and Kirmani, Sean and Ichter, Brian and Driess, Danny and Florence, Pete and Sadigh, Dorsa and Guibas, Leonidas and Xia, Fei},
|
||||
journal = {arXiv preprint arXiv:2401.12168},
|
||||
year = {2024},
|
||||
url = {https://arxiv.org/abs/2401.12168},
|
||||
}
|
||||
|
||||
@misc{qwen2.5-VL,
|
||||
title = {Qwen2.5-VL},
|
||||
url = {https://qwenlm.github.io/blog/qwen2.5-vl/},
|
||||
author = {Qwen Team},
|
||||
month = {January},
|
||||
year = {2025}
|
||||
}
|
||||
|
||||
@article{wu2025spatialscore,
|
||||
author = {Wu, Haoning and Huang, Xiao and Chen, Yaohui and Zhang, Ya and Wang, Yanfeng and Xie, Weidi},
|
||||
title = {SpatialScore: Towards Unified Evaluation for Multimodal Spatial Understanding},
|
||||
journal = {arXiv preprint arXiv:2505.17012},
|
||||
year = {2025},
|
||||
}
|
||||
|
||||
@article{omnispatial25,
|
||||
title = {OmniSpatial: Towards Comprehensive Spatial Reasoning Benchmark for Vision Language Models},
|
||||
author = {Mengdi Jia and Zekun Qi and Shaochen Zhang and Wenyao Zhang and Xinqiang Yu and Jiawei He and He Wang and Li Yi},
|
||||
journal = {arXiv preprint arXiv:2506.03135},
|
||||
year = {2025}
|
||||
}
|
||||
|
||||
@article{song2025siribench,
|
||||
title = {{SIRI-Bench}: Challenging VLMs’ Spatial Intelligence through Complex Reasoning Tasks},
|
||||
author = {Song, Zijian and Lin, Xiaoxin and Huang, Qiuming and Wang, Guangrun and Lin, Liang},
|
||||
journal = {arXiv preprint arXiv:2506.14512},
|
||||
year = {2025},
|
||||
url = {https://arxiv.org/abs/2506.14512}
|
||||
}
|
||||
|
||||
@misc{yin2025spatial,
|
||||
title = {Spatial Mental Modeling from Limited Views},
|
||||
author = {Baiqiao Yin and Qineng Wang and Pingyue Zhang and Jianshu Zhang
|
||||
and Kangrui Wang and Zihan Wang and Jieyu Zhang
|
||||
and Keshigeyan Chandrasegaran and Han Liu and Ranjay Krishna
|
||||
and Saining Xie and Manling Li and Jiajun Wu and Li Fei-Fei},
|
||||
year = {2025},
|
||||
archivePrefix= {arXiv},
|
||||
eprint = {2506.21458},
|
||||
primaryClass = {cs.AI},
|
||||
url = {https://arxiv.org/abs/2506.21458}
|
||||
}
|
||||
|
||||
```
|
||||
3
SpaceQwen2.5-VL-3B-Instruct-F16.gguf
Normal file
3
SpaceQwen2.5-VL-3B-Instruct-F16.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:1e42dcc98b2cea4c987c45c13cd8b3fe8f2f9c18b757ef8e2ccb77993f9021c9
|
||||
size 6178317312
|
||||
24
added_tokens.json
Normal file
24
added_tokens.json
Normal file
@@ -0,0 +1,24 @@
|
||||
{
|
||||
"</tool_call>": 151658,
|
||||
"<tool_call>": 151657,
|
||||
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|
||||
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|
||||
"<|endoftext|>": 151643,
|
||||
"<|file_sep|>": 151664,
|
||||
"<|fim_middle|>": 151660,
|
||||
"<|fim_pad|>": 151662,
|
||||
"<|fim_prefix|>": 151659,
|
||||
"<|fim_suffix|>": 151661,
|
||||
"<|im_end|>": 151645,
|
||||
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|
||||
"<|image_pad|>": 151655,
|
||||
"<|object_ref_end|>": 151647,
|
||||
"<|object_ref_start|>": 151646,
|
||||
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|
||||
"<|quad_start|>": 151650,
|
||||
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|
||||
"<|video_pad|>": 151656,
|
||||
"<|vision_end|>": 151653,
|
||||
"<|vision_pad|>": 151654,
|
||||
"<|vision_start|>": 151652
|
||||
}
|
||||
3
assets/SpaceLLaVA.pdf
Normal file
3
assets/SpaceLLaVA.pdf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:08a1ee6adc1b3e6649ac509e9438287577976bb991c7360110ca5d8dace55ee3
|
||||
size 3735716
|
||||
3
chat_template.json
Normal file
3
chat_template.json
Normal file
@@ -0,0 +1,3 @@
|
||||
{
|
||||
"chat_template": "{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n{% endif %}<|im_start|>{{ message['role'] }}\n{% if message['content'] is string %}{{ message['content'] }}<|im_end|>\n{% else %}{% for content in message['content'] %}{% if content['type'] == 'image' or 'image' in content or 'image_url' in content %}{% set image_count.value = image_count.value + 1 %}{% if add_vision_id %}Picture {{ image_count.value }}: {% endif %}<|vision_start|><|image_pad|><|vision_end|>{% elif content['type'] == 'video' or 'video' in content %}{% set video_count.value = video_count.value + 1 %}{% if add_vision_id %}Video {{ video_count.value }}: {% endif %}<|vision_start|><|video_pad|><|vision_end|>{% elif 'text' in content %}{{ content['text'] }}{% endif %}{% endfor %}<|im_end|>\n{% endif %}{% endfor %}{% if add_generation_prompt %}<|im_start|>assistant\n{% endif %}"
|
||||
}
|
||||
51
config.json
Normal file
51
config.json
Normal file
@@ -0,0 +1,51 @@
|
||||
{
|
||||
"_name_or_path": "Qwen/Qwen2.5-VL-3B-Instruct",
|
||||
"architectures": [
|
||||
"Qwen2_5_VLForConditionalGeneration"
|
||||
],
|
||||
"attention_dropout": 0.0,
|
||||
"bos_token_id": 151643,
|
||||
"eos_token_id": 151645,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 2048,
|
||||
"image_token_id": 151655,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 11008,
|
||||
"max_position_embeddings": 128000,
|
||||
"max_window_layers": 70,
|
||||
"model_type": "qwen2_5_vl",
|
||||
"num_attention_heads": 16,
|
||||
"num_hidden_layers": 36,
|
||||
"num_key_value_heads": 2,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_scaling": {
|
||||
"mrope_section": [
|
||||
16,
|
||||
24,
|
||||
24
|
||||
],
|
||||
"rope_type": "default",
|
||||
"type": "default"
|
||||
},
|
||||
"rope_theta": 1000000.0,
|
||||
"sliding_window": 32768,
|
||||
"tie_word_embeddings": true,
|
||||
"torch_dtype": "float16",
|
||||
"transformers_version": "4.49.0.dev0",
|
||||
"use_cache": true,
|
||||
"use_sliding_window": false,
|
||||
"video_token_id": 151656,
|
||||
"vision_config": {
|
||||
"hidden_size": 1280,
|
||||
"in_chans": 3,
|
||||
"model_type": "qwen2_5_vl",
|
||||
"out_hidden_size": 2048,
|
||||
"spatial_patch_size": 14,
|
||||
"tokens_per_second": 2,
|
||||
"torch_dtype": "float16"
|
||||
},
|
||||
"vision_end_token_id": 151653,
|
||||
"vision_start_token_id": 151652,
|
||||
"vision_token_id": 151654,
|
||||
"vocab_size": 151936
|
||||
}
|
||||
1
configuration.json
Normal file
1
configuration.json
Normal file
@@ -0,0 +1 @@
|
||||
{"framework": "pytorch", "task": "image-text-to-text", "allow_remote": true}
|
||||
14
generation_config.json
Normal file
14
generation_config.json
Normal file
@@ -0,0 +1,14 @@
|
||||
{
|
||||
"bos_token_id": 151643,
|
||||
"do_sample": true,
|
||||
"eos_token_id": [
|
||||
151645,
|
||||
151643
|
||||
],
|
||||
"pad_token_id": 151643,
|
||||
"repetition_penalty": 1.05,
|
||||
"temperature": 0.1,
|
||||
"top_k": 1,
|
||||
"top_p": 0.001,
|
||||
"transformers_version": "4.49.0.dev0"
|
||||
}
|
||||
BIN
merges.txt
(Stored with Git LFS)
Normal file
BIN
merges.txt
(Stored with Git LFS)
Normal file
Binary file not shown.
3
model-00001-of-00002.safetensors
Normal file
3
model-00001-of-00002.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:304f1da379cbe9e4a1f9ce2337f8ddd3f341d433156c921ab270cb1ad68f95c7
|
||||
size 4997750128
|
||||
3
model-00002-of-00002.safetensors
Normal file
3
model-00002-of-00002.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
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|
||||
size 2511586992
|
||||
831
model.safetensors.index.json
Normal file
831
model.safetensors.index.json
Normal file
@@ -0,0 +1,831 @@
|
||||
{
|
||||
"metadata": {
|
||||
"total_size": 7509245952
|
||||
},
|
||||
"weight_map": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"model.layers.0.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"model.layers.1.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
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19
preprocessor_config.json
Normal file
19
preprocessor_config.json
Normal file
@@ -0,0 +1,19 @@
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{
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3
spaceqwen2.5-vl-3b-instruct-vision.gguf
Normal file
3
spaceqwen2.5-vl-3b-instruct-vision.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:80d2af097ad99b8ccd77eb824e697338905e723eb32676e4c40c375b32c26573
|
||||
size 2674769152
|
||||
31
special_tokens_map.json
Normal file
31
special_tokens_map.json
Normal file
@@ -0,0 +1,31 @@
|
||||
{
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"eos_token": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:9c5ae00e602b8860cbd784ba82a8aa14e8feecec692e7076590d014d7b7fdafa
|
||||
size 11421896
|
||||
209
tokenizer_config.json
Normal file
209
tokenizer_config.json
Normal file
@@ -0,0 +1,209 @@
|
||||
{
|
||||
"add_bos_token": false,
|
||||
"add_prefix_space": false,
|
||||
"added_tokens_decoder": {
|
||||
"151643": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151644": {
|
||||
"content": "<|im_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151645": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151646": {
|
||||
"content": "<|object_ref_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151647": {
|
||||
"content": "<|object_ref_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151648": {
|
||||
"content": "<|box_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151649": {
|
||||
"content": "<|box_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151650": {
|
||||
"content": "<|quad_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151651": {
|
||||
"content": "<|quad_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151652": {
|
||||
"content": "<|vision_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151653": {
|
||||
"content": "<|vision_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151654": {
|
||||
"content": "<|vision_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151655": {
|
||||
"content": "<|image_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151656": {
|
||||
"content": "<|video_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151657": {
|
||||
"content": "<tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151658": {
|
||||
"content": "</tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151659": {
|
||||
"content": "<|fim_prefix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151660": {
|
||||
"content": "<|fim_middle|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151661": {
|
||||
"content": "<|fim_suffix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151662": {
|
||||
"content": "<|fim_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151663": {
|
||||
"content": "<|repo_name|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151664": {
|
||||
"content": "<|file_sep|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are a helpful assistant.' }}\n {%- endif %}\n {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n {%- if messages[0]['role'] == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n {%- else %}\n {{- '<|im_start|>system\\nYou are a helpful assistant.<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- message.content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": {},
|
||||
"model_max_length": 131072,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"processor_class": "Qwen2_5_VLProcessor",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
BIN
vocab.json
(Stored with Git LFS)
Normal file
BIN
vocab.json
(Stored with Git LFS)
Normal file
Binary file not shown.
Reference in New Issue
Block a user