Upload MolmoForCausalLM
Browse files- config.json +48 -0
- config_molmo.py +60 -0
- generation_config.json +4 -0
- model-00001-of-00002.safetensors +3 -0
- model-00002-of-00002.safetensors +3 -0
- model.safetensors.index.json +0 -0
- modeling_molmo.py +0 -0
config.json
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{
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"_name_or_path": "/4bit",
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"architectures": [
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"MolmoForCausalLM"
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],
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"attention_layer_norm": true,
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"auto_map": {
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"AutoConfig": "config_molmo.MolmoConfig",
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"AutoModelForCausalLM": "modeling_molmo.MolmoForCausalLM"
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},
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"clip_qkv": null,
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"embedding_size": 100352,
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 22016,
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"layer_norm_eps": 1e-06,
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"layer_norm_type": "rms",
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"max_position_embeddings": 4096,
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"model_type": "molmo",
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"norm_after": true,
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": null,
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"qkv_bias": false,
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"quantization_config": {
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"_load_in_4bit": true,
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"_load_in_8bit": false,
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"bnb_4bit_compute_dtype": "float32",
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"bnb_4bit_quant_storage": "uint8",
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"bnb_4bit_quant_type": "fp4",
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"bnb_4bit_use_double_quant": true,
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"llm_int8_enable_fp32_cpu_offload": false,
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"llm_int8_has_fp16_weight": false,
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"llm_int8_skip_modules": null,
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"llm_int8_threshold": 6.0,
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"load_in_4bit": true,
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"load_in_8bit": false,
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"quant_method": "bitsandbytes"
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},
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"rope_theta": 500000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "float32",
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"transformers_version": "4.44.0",
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"use_cache": true,
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"use_position_ids": true,
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"vocab_size": 100278,
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"weight_tying": false
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}
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config_molmo.py
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from typing import List
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from transformers import PretrainedConfig, AutoTokenizer
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class MolmoConfig(PretrainedConfig):
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model_type = "molmo"
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keys_to_ignore_at_inference = ["past_key_values"]
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def __init__(
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self,
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vocab_size=50304,
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embedding_size=50304,
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hidden_size=4096,
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intermediate_size=11008,
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num_hidden_layers=32,
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num_attention_heads=32,
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num_key_value_heads=None,
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max_position_embeddings=2048,
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initializer_range=0.02,
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use_cache=True,
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layer_norm_eps: float = 1e-5,
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rope_theta=10000.0,
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clip_qkv=None,
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qkv_bias: bool = False,
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weight_tying: bool = False,
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use_position_ids: bool=True,
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tie_word_embeddings: bool=True,
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attention_layer_norm: bool=False,
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norm_after: bool = False,
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layer_norm_type: str="rms",
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**kwargs,
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):
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self.vocab_size = vocab_size
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self.embedding_size = embedding_size
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self.max_position_embeddings = max_position_embeddings
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self.hidden_size = hidden_size
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self.intermediate_size = intermediate_size
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self.num_hidden_layers = num_hidden_layers
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self.num_attention_heads = num_attention_heads
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self.layer_norm_eps = layer_norm_eps
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self.weight_tying = weight_tying
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self.use_position_ids = use_position_ids
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self.attention_layer_norm = attention_layer_norm
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self.num_key_value_heads = num_key_value_heads
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self.initializer_range = initializer_range
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self.use_cache = use_cache
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self.rope_theta = rope_theta
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self.clip_qkv = clip_qkv
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self.qkv_bias = qkv_bias
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self.norm_after = norm_after
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self.tie_word_embeddings = tie_word_embeddings
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self.layer_norm_type = layer_norm_type
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super().__init__(
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tie_word_embeddings=tie_word_embeddings,
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**kwargs,
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)
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MolmoConfig.register_for_auto_class()
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generation_config.json
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{
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"_from_model_config": true,
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"transformers_version": "4.44.0"
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}
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model-00001-of-00002.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:f08572c70e5685f0ae366c77094bc8efc838a86e7ca98097bb7154f8182e837c
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size 4989420502
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model-00002-of-00002.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:829dad3532317dcfbe6cc3ac42b7fa53805740bba43f567b2860a1349af1932b
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size 1836442908
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model.safetensors.index.json
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modeling_molmo.py
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