Robotics
Transformers
Safetensors
English
molmoact2
image-text-to-text
OpenRAL
rskill
vision-language-action
nf4
4-bit precision
so100_follower
so101_follower
vla
so101
so100
manipulation
custom_code
8-bit precision
Instructions to use OpenRAL/rskill-molmoact2-multi-so101-nf4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenRAL/rskill-molmoact2-multi-so101-nf4 with Transformers:
# Load model directly from transformers import AutoModelForImageTextToText model = AutoModelForImageTextToText.from_pretrained("OpenRAL/rskill-molmoact2-multi-so101-nf4", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 4,271 Bytes
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"qk_norm_eps": 1e-06,
"rope": true,
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},
"action_expert_depth_gate": false,
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]
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"add_setup_tokens": true,
"architectures": [
"MolmoAct2ForConditionalGeneration"
],
"auto_map": {
"AutoConfig": "configuration_molmoact2.MolmoAct2Config",
"AutoModelForImageTextToText": "modeling_molmoact2.MolmoAct2ForConditionalGeneration"
},
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"mask_action_dim_padding": true,
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"model_type": "molmoact2",
"n_obs_steps": 1,
"norm_stats_filename": "norm_stats.json",
"num_action_tokens": 2048,
"num_depth_codes": 100,
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"state_end_token_id": 151674,
"state_format": "discrete",
"state_start_token_id": 151673,
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"text_config": {
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"attention_dropout": 0.0,
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"residual_dropout": 0.0
},
"bos_token_id": 151645,
"eos_token_id": 151645,
"pad_token_id": 151643
}
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