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prithivMLmods
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Model Details
Model Provider
prithivMLmods
Model Tree
Qwen/Qwen2.5-VL-7B-Instruct
Input Modalities
Output Modalities
Supported Functionality
Clone the repository:
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git clone https://github.com/PRITHIVSAKTHIUR/Gliese-CUA-Tool-Call-8B-Demo.gitcd Gliese-CUA-Tool-Call-8B-DemoInstall dependencies:
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pip install -r requirements.txtStart the application:
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python app.pyClone the repository:
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git clone https://github.com/PRITHIVSAKTHIUR/Gliese-CUA-Tool-Call-8B-Localization.gitcd Gliese-CUA-Tool-Call-8B-LocalizationInstall dependencies:
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pip install -r requirements.txtStart the application:
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python app.pypython
from transformers import Qwen2_5_VLForConditionalGeneration, AutoProcessorfrom qwen_vl_utils import process_vision_info model = Qwen2_5_VLForConditionalGeneration.from_pretrained( "prithivMLmods/Gliese-CUA-Tool-Call-8B", torch_dtype="auto", device_map="auto") processor = AutoProcessor.from_pretrained("prithivMLmods/Gliese-CUA-Tool-Call-8B") messages = [ { "role": "user", "content": [ {"type": "image", "image": "<SCREENSHOT_OR_UI_IMAGE>"}, {"type": "text", "text": "Enable dark mode from the settings menu."}, ], }] 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") generated_ids = model.generate(**inputs, max_new_tokens=1024)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)Qwen2.5-VL Technical Report: https://huggingface.co/papers/2502.13923
YaRN: Efficient Context Window Extension
https://arxiv.org/pdf/2309.00071
Qwen2 VL: High Resolution Perception
https://arxiv.org/pdf/2409.12191
Model Soups: Averaging Weights of Multiple Fine-Tuned Models Improves Accuracy Without Increasing Inference Time
https://arxiv.org/abs/2203.05482
Model Stock: All We Need Is Just a Few Fine-Tuned Models
https://arxiv.org/abs/2403.19522
from transformers import Qwen2_5_VLForConditionalGeneration, AutoProcessorfrom qwen_vl_utils import process_vision_info model = Qwen2_5_VLForConditionalGeneration.from_pretrained( "prithivMLmods/Gliese-CUA-Tool-Call-8B", torch_dtype="auto", device_map="auto") processor = AutoProcessor.from_pretrained("prithivMLmods/Gliese-CUA-Tool-Call-8B") messages = [ { "role": "user", "content": [ {"type": "image", "image": "<SCREENSHOT_OR_UI_IMAGE>"}, {"type": "text", "text": "Enable dark mode from the settings menu."}, ], }] 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") generated_ids = model.generate(**inputs, max_new_tokens=1024)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)