Image-Text-to-Text
PEFT
Safetensors
Transformers
lora
orthopaedic-surgery
frame-captioning
conversational
Instructions to use rbryant19/opscribe-captioner-ortho-tool-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use rbryant19/opscribe-captioner-ortho-tool-v2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-VL-72B-Instruct") model = PeftModel.from_pretrained(base_model, "rbryant19/opscribe-captioner-ortho-tool-v2") - Transformers
How to use rbryant19/opscribe-captioner-ortho-tool-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="rbryant19/opscribe-captioner-ortho-tool-v2") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("rbryant19/opscribe-captioner-ortho-tool-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use rbryant19/opscribe-captioner-ortho-tool-v2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "rbryant19/opscribe-captioner-ortho-tool-v2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rbryant19/opscribe-captioner-ortho-tool-v2", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/rbryant19/opscribe-captioner-ortho-tool-v2
- SGLang
How to use rbryant19/opscribe-captioner-ortho-tool-v2 with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "rbryant19/opscribe-captioner-ortho-tool-v2" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rbryant19/opscribe-captioner-ortho-tool-v2", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "rbryant19/opscribe-captioner-ortho-tool-v2" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rbryant19/opscribe-captioner-ortho-tool-v2", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Docker Model Runner
How to use rbryant19/opscribe-captioner-ortho-tool-v2 with Docker Model Runner:
docker model run hf.co/rbryant19/opscribe-captioner-ortho-tool-v2
SVD merge: voiceover_v1 (0.40) + captioner_v2 (0.60) → rank 32
Browse files- .gitattributes +1 -0
- README.md +27 -0
- adapter_config.json +48 -0
- adapter_model.safetensors +3 -0
- chat_template.jinja +7 -0
- processor_config.json +31 -0
- tokenizer.json +3 -0
- tokenizer_config.json +32 -0
.gitattributes
CHANGED
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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base_model: Qwen/Qwen2.5-VL-72B-Instruct
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library_name: peft
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pipeline_tag: image-text-to-text
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tags:
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- base_model:adapter:Qwen/Qwen2.5-VL-72B-Instruct
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- lora
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- transformers
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- orthopaedic-surgery
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- frame-captioning
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---
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# opscribe-captioner-ortho-tool-v2
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SVD task arithmetic merge for Qwen2.5-VL-72B-Instruct surgical frame captioning.
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| Adapter | Weight | Rank | Data |
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|---|---|---|---|
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| captioner_voiceover_v1 | 0.40 | 16 | Surgeon-narrated ortho voiceover dataset — general captioning |
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| captioner_v2 | 0.60 | 32 | Targeted v2 dataset (793 train) — priority-tool pass for mallet, reamer, Bovie, saw |
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Merged to rank 32 (alpha=32, scale=1.0) via efficient thin-SVD task arithmetic.
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## Training Details
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- captioner_v2 best val_loss: 0.0963 (3 epochs)
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- Hardware: 4× NVIDIA H200, device_map=auto, bf16
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- LoRA targets: q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
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adapter_config.json
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{
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"alora_invocation_tokens": null,
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"alpha_pattern": {},
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"arrow_config": null,
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"auto_mapping": null,
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"base_model_name_or_path": "Qwen/Qwen2.5-VL-72B-Instruct",
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"bias": "none",
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"corda_config": null,
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"ensure_weight_tying": false,
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"eva_config": null,
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"exclude_modules": null,
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 32,
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"lora_bias": false,
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"lora_dropout": 0.05,
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"lora_ga_config": null,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"peft_version": "0.19.0",
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"qalora_group_size": 16,
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"r": 32,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"v_proj",
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"k_proj",
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"gate_proj",
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"down_proj",
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"o_proj",
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"up_proj",
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"q_proj"
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],
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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"trainable_token_indices": null,
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| 44 |
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"use_bdlora": null,
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"use_dora": false,
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| 46 |
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"use_qalora": false,
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"use_rslora": false
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}
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:2fe22aae76fe59f17a9f2a1f147635cac7d6d307b9036334821d61dde1fd4652
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size 1742667800
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chat_template.jinja
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{% 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
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You are a helpful assistant.<|im_end|>
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{% endif %}<|im_start|>{{ message['role'] }}
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{% if message['content'] is string %}{{ message['content'] }}<|im_end|>
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{% 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|>
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{% endif %}{% endfor %}{% if add_generation_prompt %}<|im_start|>assistant
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{% endif %}
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processor_config.json
ADDED
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{
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"image_processor": {
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"do_convert_rgb": true,
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"do_normalize": true,
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"do_rescale": true,
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"do_resize": true,
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"image_mean": [
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0.48145466,
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0.4578275,
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0.40821073
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],
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"image_processor_type": "Qwen2VLImageProcessor",
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"image_std": [
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0.26862954,
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0.26130258,
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0.27577711
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],
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| 18 |
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"max_pixels": 1003520,
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| 19 |
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"merge_size": 2,
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"min_pixels": 200704,
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"patch_size": 14,
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| 22 |
+
"resample": 3,
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| 23 |
+
"rescale_factor": 0.00392156862745098,
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| 24 |
+
"size": {
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| 25 |
+
"longest_edge": 1003520,
|
| 26 |
+
"shortest_edge": 200704
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},
|
| 28 |
+
"temporal_patch_size": 2
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},
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"processor_class": "Qwen2_5_VLProcessor"
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}
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tokenizer.json
ADDED
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version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:1a7aabe7a3b44651592a99607bb33066e6965260336be9218cccd53af161491d
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size 11422060
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tokenizer_config.json
ADDED
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@@ -0,0 +1,32 @@
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{
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| 2 |
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"add_prefix_space": false,
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"backend": "tokenizers",
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| 4 |
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"bos_token": null,
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| 5 |
+
"clean_up_tokenization_spaces": false,
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| 6 |
+
"eos_token": "<|im_end|>",
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| 7 |
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"errors": "replace",
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| 8 |
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"extra_special_tokens": [
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| 9 |
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"<|im_start|>",
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| 10 |
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"<|im_end|>",
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| 11 |
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"<|object_ref_start|>",
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| 12 |
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"<|object_ref_end|>",
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| 13 |
+
"<|box_start|>",
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| 14 |
+
"<|box_end|>",
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| 15 |
+
"<|quad_start|>",
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| 16 |
+
"<|quad_end|>",
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| 17 |
+
"<|vision_start|>",
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| 18 |
+
"<|vision_end|>",
|
| 19 |
+
"<|vision_pad|>",
|
| 20 |
+
"<|image_pad|>",
|
| 21 |
+
"<|video_pad|>"
|
| 22 |
+
],
|
| 23 |
+
"is_local": true,
|
| 24 |
+
"max_pixels": 1003520,
|
| 25 |
+
"min_pixels": 200704,
|
| 26 |
+
"model_max_length": 131072,
|
| 27 |
+
"pad_token": "<|endoftext|>",
|
| 28 |
+
"processor_class": "Qwen2_5_VLProcessor",
|
| 29 |
+
"split_special_tokens": false,
|
| 30 |
+
"tokenizer_class": "Qwen2Tokenizer",
|
| 31 |
+
"unk_token": null
|
| 32 |
+
}
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