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--- |
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base_model: |
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- microsoft/Florence-2-base-ft |
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datasets: |
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- salma-remyx/PoseText |
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library_name: transformers |
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tags: |
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- remyx |
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- PoseEstimation |
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- TextGeneration |
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- MultiModal |
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- VLM |
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--- |
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# Model Card for PoseFlorence-2 |
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This model fine-tunes Florence-2-base-ft in the POSE task for body keypoint estimation using the PoseText Dataset. |
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# Running PoseFlorence-2 |
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```python |
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import requests |
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import torch |
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from PIL import Image |
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from transformers import AutoProcessor, AutoModelForCausalLM |
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device = "cuda:0" if torch.cuda.is_available() else "cpu" |
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torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32 |
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model = AutoModelForCausalLM.from_pretrained("remyxai/PoseeFlorence-2", trust_remote_code=True).to(device) |
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processor = AutoProcessor.from_pretrained("remyxai/PoseFlorence-2", trust_remote_code=True) |
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prompt = "<POSE>" |
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url = "https://remyx.ai/assets/spatialvlm/warehouse_rgb.jpg?download=true" |
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image = Image.open(requests.get(url, stream=True).raw) |
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inputs = processor(text=prompt, images=image, return_tensors="pt").to(device, torch_dtype) |
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generated_ids = model.generate( |
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input_ids=inputs["input_ids"], |
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pixel_values=inputs["pixel_values"], |
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max_new_tokens=1024, |
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num_beams=3, |
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do_sample=False |
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) |
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generated_text = processor.batch_decode(generated_ids, skip_special_tokens=False)[0] |
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parsed_answer = processor.post_process_generation(generated_text, task=prompt, image_size=(image.width, image.height)) |
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print(parsed_answer) |
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``` |
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- **Developed by:** [remyx.ai] |
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- **Finetuned from model:** [microsoft/Florence-2-base-ft] |
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