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Initializing ImageBind encoder ... ... ImageBind encoder initialized. Initializing Reasoner LLM model and tokenizer ... Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. ... tokenizer initialized. Freezing the Reasoner ... ... Reasoner LLM model initialized. Initializing input ImageBind Projection ... ... Input ImageBind Projection initialized text prompt: <|im_start|>system You are a assistant<|im_end|> <|im_start|>user Describe the image and audio: <|im_start|>system You are a assistant<|im_end|> <|im_start|>user Describe the image and audio: <|image_start|> <|audio_start|> recieved image Encoding Image [tensor([[[-2.0294e-03, 2.0996e-02, -1.3672e-02, -1.1475e-02, -1.9836e-03, 9.7656e-03, -1.2451e-02, 8.0566e-03, -6.6757e-04, -7.4768e-04, 1.3794e-02, 7.3853e-03, -2.2461e-02, 8.4305e-04, -2.1973e-02, 8.3008e-03, 2.3193e-02, 1.3733e-02, -2.3926e-02, -2.3346e-03, 3.5889e-02, 6.4697e-03, -1.2695e-02, 4.5471e-03, 2.0264e-02, 9.9487e-03, 1.1841e-02, -1.5137e-02, 1.3672e-02, -1.9653e-02, -6.3782e-03, 1.8921e-03, -3.6774e-03, 1.3672e-02, 5.3101e-03, -2.3682e-02, 1.3245e-02, 1.2756e-02, 1.5182e-03, -4.6997e-03, 1.5198e-02, 8.2397e-03, -1.0986e-02, 6.5918e-03, -4.6158e-04, 1.0498e-02, 3.4027e-03, 1.6556e-03, 7.1716e-03, -3.3875e-03, 2.9297e-03, 4.3945e-03, -3.4332e-03, 5.7068e-03, 3.8910e-03, 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0.0060, -0.0280, 0.0079, ..., -0.0086, 0.0168, 0.0135], [ 0.0121, 0.0053, -0.0028, ..., 0.0192, 0.0135, 0.0059], ..., [ 0.0245, 0.0073, 0.0044, ..., 0.0104, -0.0150, -0.0141], [ 0.0060, -0.0280, 0.0079, ..., -0.0086, 0.0168, 0.0135], [ 0.0123, -0.0060, 0.0310, ..., 0.0021, 0.0104, 0.0239]]], grad_fn=<CatBackward0>)] Generaded and Prepared the inputs: tensor([[[-0.0020, 0.0210, -0.0137, ..., 0.0057, -0.0184, 0.0120], [-0.0020, 0.0210, -0.0137, ..., 0.0057, -0.0184, 0.0120], [-0.0120, -0.0040, 0.0083, ..., 0.0083, 0.0131, -0.0119], ..., [ 0.0123, -0.0060, 0.0310, ..., 0.0021, 0.0104, 0.0239], [-0.0020, 0.0210, -0.0137, ..., 0.0057, -0.0184, 0.0120], [-0.0030, -0.0425, 0.0232, ..., 0.0081, 0.0537, -0.0090]]], grad_fn=<CatBackward0>) Generates IDs from the Reasoner: tensor([[ 362, 883, 374, 11699, 389, 264, 13425, 11, 9963, 264, 3460, 91613, 315, 19281, 13, 576, 6249, 15562, 82, 304, 389, 279, 883, 594, 3579, 323, 279, 91613, 438, 566, 9982, 432, 705, 13, 576, 5112, 6239, 369, 19281, 323, 7203, 525, 59021, 11, 18860, 429, 419, 6109, 374, 4363]]) Tokenized the Outputs A man is sitting on a bench, holding a large bouquet of flowers. The camera zooms in on the man's face and the bouquet as he holds it up. The sound effects for flowers and movement are muted, indicating that this scene is likely |