Instructions to use Dimios45/yam-world-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use Dimios45/yam-world-model with LeRobot:
- Notebooks
- Google Colab
- Kaggle
abc12/tokenizer step 24000: model
Browse files- .gitattributes +4 -0
- abc12/tokenizer/model/24000/_CHECKPOINT_METADATA +1 -0
- abc12/tokenizer/model/24000/config/metadata +1 -0
- abc12/tokenizer/model/24000/variables/_METADATA +1 -0
- abc12/tokenizer/model/24000/variables/_sharding +1 -0
- abc12/tokenizer/model/24000/variables/array_metadatas/process_0 +1 -0
- abc12/tokenizer/model/24000/variables/d/d23e0782d31d04f715bf777b7a4b1e4d +0 -0
- abc12/tokenizer/model/24000/variables/manifest.ocdbt +0 -0
- abc12/tokenizer/model/24000/variables/ocdbt.process_0/d/065fe935165cd9f43389bb60f40cb57c +0 -0
- abc12/tokenizer/model/24000/variables/ocdbt.process_0/d/1705fddf847c3c6693df0531c4d59f9b +3 -0
- abc12/tokenizer/model/24000/variables/ocdbt.process_0/d/296a950b38562c3c93b41e57e2f6b82a +3 -0
- abc12/tokenizer/model/24000/variables/ocdbt.process_0/d/335758bedf4d78398fa7fa50a6283c5a +0 -0
- abc12/tokenizer/model/24000/variables/ocdbt.process_0/d/61ba7c2deaa47a14beaf35c7823cfeed +3 -0
- abc12/tokenizer/model/24000/variables/ocdbt.process_0/d/92eab98de33f3783d8318b7b72fee75c +0 -0
- abc12/tokenizer/model/24000/variables/ocdbt.process_0/d/ec5a73e3b3759dcbf1eff5d04b83cb17 +3 -0
- abc12/tokenizer/model/24000/variables/ocdbt.process_0/manifest.ocdbt +0 -0
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{"item_handlers": {"config": "orbax.checkpoint._src.handlers.json_checkpoint_handler.JsonCheckpointHandler", "variables": "orbax.checkpoint._src.handlers.standard_checkpoint_handler.StandardCheckpointHandler"}, "metrics": {}, "performance_metrics": {}, "init_timestamp_nsecs": 1787454045452078785, "commit_timestamp_nsecs": 1787454045808830132, "custom_metadata": {}}
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{"_target_": "visionary.models.dreamer4.tokenizer.Tokenizer", "encoder_num_layers": 8, "encoder_num_heads": 8, "encoder_num_kv_heads": 2, "encoder_model_dim": 512, "encoder_mlp_hidden_dim": 1536, "decoder_num_layers": 8, "decoder_num_heads": 8, "decoder_num_kv_heads": 2, "decoder_model_dim": 512, "decoder_mlp_hidden_dim": 1536, "num_latents": 192, "head_dim": 64, "channel_dim": 24, "temporal_layer_period": 4, "temporal_layer_offset": 1, "resize_shape": [144, 192], "pad_width": [0, 0], "patch_size": 16, "base": 10000.0, "independent_prob": 0.2, "remat_policy": "dots_with_no_batch_dims_saveable"}
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abc12/tokenizer/model/24000/variables/_sharding
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