Upload folder using huggingface_hub
Browse files- .gitattributes +1 -0
- README.md +91 -0
- added_tokens.json +3 -0
- chat_template.json +3 -0
- config.json +60 -0
- generation_config.json +11 -0
- model.safetensors +3 -0
- preprocessor_config.json +29 -0
- processor_config.json +4 -0
- special_tokens_map.json +33 -0
- tokenizer.json +3 -0
- tokenizer.model +3 -0
- tokenizer_config.json +0 -0
.gitattributes
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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library_name: transformers
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pipeline_tag: image-text-to-text
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inference: true
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widget:
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- text: Hello!
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example_title: Hello world
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group: Python
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---
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This tiny model is for debugging. It is randomly initialized with the config adapted from [google/gemma-3-27b-it](https://huggingface.co/google/gemma-3-27b-it).
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### Example usage:
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```python
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from transformers import pipeline
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model_id = "tiny-random/gemma-3"
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pipe = pipeline(
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"image-text-to-text", model=model_id, device="cuda",
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trust_remote_code=True, max_new_tokens=3,
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)
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messages = [
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{
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"role": "system",
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"content": [{"type": "text", "text": "You are a helpful assistant."}]
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},
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{
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"role": "user",
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"content": [
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{"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
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{"type": "text", "text": "What animal is on the candy?"}
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]
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}
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]
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output = pipe(text=messages, max_new_tokens=5)
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print(output)
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```
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### Codes to create this repo:
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```python
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import torch
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from transformers import (
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AutoConfig,
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AutoModelForCausalLM,
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AutoProcessor,
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AutoTokenizer,
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Gemma3ForConditionalGeneration,
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GenerationConfig,
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pipeline,
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set_seed,
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)
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source_model_id = "google/gemma-3-27b-it"
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save_folder = "/tmp/tiny-random/gemma-3"
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processor = AutoProcessor.from_pretrained(
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source_model_id, trust_remote_code=True,
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)
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processor.save_pretrained(save_folder)
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config = AutoConfig.from_pretrained(
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source_model_id, trust_remote_code=True,
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)
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config.text_config.hidden_size = 32
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config.text_config.intermediate_size = 128
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config.text_config.head_dim = 32
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config.text_config.num_attention_heads = 1
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config.text_config.num_key_value_heads = 1
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config.text_config.num_hidden_layers = 2
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config.text_config.sliding_window_pattern = 2
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config.vision_config.hidden_size = 32
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config.vision_config.num_hidden_layers = 2
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config.vision_config.num_attention_heads = 1
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config.vision_config.intermediate_size = 128
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model = Gemma3ForConditionalGeneration(
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config,
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).to(torch.bfloat16)
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for layer in model.language_model.model.layers:
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print(layer.is_sliding)
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model.generation_config = GenerationConfig.from_pretrained(
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source_model_id, trust_remote_code=True,
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)
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set_seed(42)
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with torch.no_grad():
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for name, p in sorted(model.named_parameters()):
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torch.nn.init.normal_(p, 0, 0.5)
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print(name, p.shape)
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model.save_pretrained(save_folder)
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```
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added_tokens.json
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{
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"<image_soft_token>": 262144
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}
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chat_template.json
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{
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"chat_template": "{{ bos_token }}\n{%- if messages[0]['role'] == 'system' -%}\n {%- if messages[0]['content'] is string -%}\n {%- set first_user_prefix = messages[0]['content'] + '\n\n' -%}\n {%- else -%}\n {%- set first_user_prefix = messages[0]['content'][0]['text'] + '\n\n' -%}\n {%- endif -%}\n {%- set loop_messages = messages[1:] -%}\n{%- else -%}\n {%- set first_user_prefix = \"\" -%}\n {%- set loop_messages = messages -%}\n{%- endif -%}\n{%- for message in loop_messages -%}\n {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}\n {{ raise_exception(\"Conversation roles must alternate user/assistant/user/assistant/...\") }}\n {%- endif -%}\n {%- if (message['role'] == 'assistant') -%}\n {%- set role = \"model\" -%}\n {%- else -%}\n {%- set role = message['role'] -%}\n {%- endif -%}\n {{ '<start_of_turn>' + role + '\n' + (first_user_prefix if loop.first else \"\") }}\n {%- if message['content'] is string -%}\n {{ message['content'] | trim }}\n {%- elif message['content'] is iterable -%}\n {%- for item in message['content'] -%}\n {%- if item['type'] == 'image' -%}\n {{ '<start_of_image>' }}\n {%- elif item['type'] == 'text' -%}\n {{ item['text'] | trim }}\n {%- endif -%}\n {%- endfor -%}\n {%- else -%}\n {{ raise_exception(\"Invalid content type\") }}\n {%- endif -%}\n {{ '<end_of_turn>\n' }}\n{%- endfor -%}\n{%- if add_generation_prompt -%}\n {{'<start_of_turn>model\n'}}\n{%- endif -%}\n"
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}
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config.json
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{
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"architectures": [
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"Gemma3ForConditionalGeneration"
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],
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"boi_token_index": 255999,
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"eoi_token_index": 256000,
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"eos_token_id": [
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1,
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106
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],
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"image_token_index": 262144,
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"initializer_range": 0.02,
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"mm_tokens_per_image": 256,
|
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"model_type": "gemma3",
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"text_config": {
|
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"attention_bias": false,
|
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"attention_dropout": 0.0,
|
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+
"attn_logit_softcapping": null,
|
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+
"cache_implementation": "hybrid",
|
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+
"final_logit_softcapping": null,
|
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+
"head_dim": 32,
|
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+
"hidden_activation": "gelu_pytorch_tanh",
|
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"hidden_size": 32,
|
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+
"initializer_range": 0.02,
|
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+
"intermediate_size": 128,
|
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+
"max_position_embeddings": 131072,
|
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+
"model_type": "gemma3_text",
|
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"num_attention_heads": 1,
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"num_hidden_layers": 2,
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"num_key_value_heads": 1,
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"query_pre_attn_scalar": 168,
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"rms_norm_eps": 1e-06,
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"rope_local_base_freq": 10000.0,
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"rope_scaling": {
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"factor": 8.0,
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"rope_type": "linear"
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},
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"rope_theta": 1000000.0,
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"sliding_window": 1024,
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"sliding_window_pattern": 2,
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"use_cache": true,
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"vocab_size": 262208
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},
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"torch_dtype": "bfloat16",
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"transformers_version": "4.50.0.dev0",
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"vision_config": {
|
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+
"attention_dropout": 0.0,
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"hidden_act": "gelu_pytorch_tanh",
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"hidden_size": 32,
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"image_size": 896,
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"intermediate_size": 128,
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"layer_norm_eps": 1e-06,
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"model_type": "siglip_vision_model",
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"num_attention_heads": 1,
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"num_channels": 3,
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"num_hidden_layers": 2,
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"patch_size": 14,
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"vision_use_head": false
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}
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 2,
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"cache_implementation": "hybrid",
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"eos_token_id": [
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1,
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106
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],
|
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"pad_token_id": 0,
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"transformers_version": "4.50.0.dev0"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:d7f723f4b5c9009b899a706e042acbfc686c3ef3db677b1909fa262263dde5f1
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size 17209104
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preprocessor_config.json
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{
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"do_convert_rgb": null,
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"do_normalize": true,
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"do_pan_and_scan": null,
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"do_rescale": true,
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"do_resize": true,
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"image_mean": [
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0.5,
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0.5,
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0.5
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],
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"image_processor_type": "Gemma3ImageProcessor",
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"image_seq_length": 256,
|
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"image_std": [
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0.5,
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0.5,
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+
0.5
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],
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"pan_and_scan_max_num_crops": null,
|
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"pan_and_scan_min_crop_size": null,
|
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"pan_and_scan_min_ratio_to_activate": null,
|
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"processor_class": "Gemma3Processor",
|
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"resample": 2,
|
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"rescale_factor": 0.00392156862745098,
|
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"size": {
|
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"height": 896,
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"width": 896
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}
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}
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processor_config.json
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{
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"image_seq_length": 256,
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"processor_class": "Gemma3Processor"
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}
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special_tokens_map.json
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{
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"boi_token": "<start_of_image>",
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"bos_token": {
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"content": "<bos>",
|
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"lstrip": false,
|
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"normalized": false,
|
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"rstrip": false,
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"single_word": false
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},
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"eoi_token": "<end_of_image>",
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"eos_token": {
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"content": "<eos>",
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"lstrip": false,
|
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"normalized": false,
|
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"rstrip": false,
|
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"single_word": false
|
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},
|
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"image_token": "<image_soft_token>",
|
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"pad_token": {
|
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"content": "<pad>",
|
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"lstrip": false,
|
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"normalized": false,
|
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"rstrip": false,
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"single_word": false
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},
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"unk_token": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": false,
|
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"rstrip": false,
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"single_word": false
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}
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}
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:4667f2089529e8e7657cfb6d1c19910ae71ff5f28aa7ab2ff2763330affad795
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size 33384568
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tokenizer.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:1299c11d7cf632ef3b4e11937501358ada021bbdf7c47638d13c0ee982f2e79c
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size 4689074
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tokenizer_config.json
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