import os os.system("pip install deepspeed") os.system("pip freeze") import gradio as gr import re from magma import Magma from magma.image_input import ImageInput from huggingface_hub import hf_hub_url, cached_download checkpoint_url = hf_hub_url(repo_id="osanseviero/magma", filename="model.pt") checkpoint_path = cached_download(checkpoint_url) model = Magma.from_checkpoint( config_path = "configs/MAGMA_v1.yml", checkpoint_path = checkpoint_path, device = 'cuda:0' ) def generate(context, length, temperature, top_k): context = context.strip() url_regex = r'https?:\/\/(www\.)?[-a-zA-Z0-9@:%._\+~#=]{1,256}\.[a-zA-Z0-9()]{1,6}\b([-a-zA-Z0-9()@:%_\+.~#?&//=]*)' lines = context.split('\n') inputs = [] for line in lines: if re.match(url_regex, line): try: inputs.append(ImageInput(line)) except Exception as e: return str(e) else: inputs.append(line) ## returns a tensor of shape: (1, 149, 4096) embeddings = model.preprocess_inputs(inputs) ## returns a list of length embeddings.shape[0] (batch size) output = model.generate( embeddings = embeddings, max_steps = length, temperature = (0.01 if temperature == 0 else temperature), top_k = top_k ) return context + output[0] iface = gr.Interface( fn=generate, inputs=[ gr.inputs.Textbox( label="Prompt (image URLs need to be on their own lines):", default="https://www.art-prints-on-demand.com/kunst/thomas_cole/woods_hi.jpg\nDescribe the painting:", lines=7), gr.inputs.Slider(minimum=1, maximum=100, default=15, step=1, label="Output tokens:"), gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.7, label='Temperature'), gr.inputs.Slider(minimum=0, maximum=100, default=0, step=1, label='Top K') ], outputs=["textbox"] ).launch(share=True)