File size: 2,559 Bytes
920fd91 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 | from transformers import Mistral3ForConditionalGeneration, Mistral3Config
class Flux2TextEncoder(Mistral3ForConditionalGeneration):
def __init__(self):
config = Mistral3Config(**{
"architectures": [
"Mistral3ForConditionalGeneration"
],
"dtype": "bfloat16",
"image_token_index": 10,
"model_type": "mistral3",
"multimodal_projector_bias": False,
"projector_hidden_act": "gelu",
"spatial_merge_size": 2,
"text_config": {
"attention_dropout": 0.0,
"dtype": "bfloat16",
"head_dim": 128,
"hidden_act": "silu",
"hidden_size": 5120,
"initializer_range": 0.02,
"intermediate_size": 32768,
"max_position_embeddings": 131072,
"model_type": "mistral",
"num_attention_heads": 32,
"num_hidden_layers": 40,
"num_key_value_heads": 8,
"rms_norm_eps": 1e-05,
"rope_theta": 1000000000.0,
"sliding_window": None,
"use_cache": True,
"vocab_size": 131072
},
"transformers_version": "4.57.1",
"vision_config": {
"attention_dropout": 0.0,
"dtype": "bfloat16",
"head_dim": 64,
"hidden_act": "silu",
"hidden_size": 1024,
"image_size": 1540,
"initializer_range": 0.02,
"intermediate_size": 4096,
"model_type": "pixtral",
"num_attention_heads": 16,
"num_channels": 3,
"num_hidden_layers": 24,
"patch_size": 14,
"rope_theta": 10000.0
},
"vision_feature_layer": -1
})
super().__init__(config)
def forward(self, input_ids = None, pixel_values = None, attention_mask = None, position_ids = None, past_key_values = None, inputs_embeds = None, labels = None, use_cache = None, output_attentions = None, output_hidden_states = None, return_dict = None, cache_position = None, logits_to_keep = 0, image_sizes = None, **kwargs):
return super().forward(input_ids, pixel_values, attention_mask, position_ids, past_key_values, inputs_embeds, labels, use_cache, output_attentions, output_hidden_states, return_dict, cache_position, logits_to_keep, image_sizes, **kwargs)
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