LewinRobin commited on
Commit
0e7b256
·
verified ·
1 Parent(s): 72b1661

Add fully merged standalone MedGemma-RoCoV2 model

Browse files
.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
36
+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,54 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ language: en
3
+ license: gemma
4
+ tags:
5
+ - medgemma
6
+ - radiology
7
+ - rocov2
8
+ - medical
9
+ - merged
10
+ base_model: google/medgemma-4b-it
11
+ datasets:
12
+ - StanfordAIMI/rocov2
13
+ ---
14
+
15
+ # MedGemma RoCoV2 — Standalone Merged Model
16
+
17
+ This is a fully merged (adapter-free) version of MedGemma fine-tuned on
18
+ [RoCoV2](https://huggingface.co/datasets/StanfordAIMI/rocov2).
19
+
20
+ The LoRA adapters from [LewinRobin/Medgemma_Rocov2](https://huggingface.co/LewinRobin/Medgemma_Rocov2)
21
+ have been merged directly into the base weights of
22
+ [google/medgemma-4b-it](https://huggingface.co/google/medgemma-4b-it).
23
+
24
+ **No PEFT dependency required** — load with plain `AutoModelForCausalLM`.
25
+
26
+ ## Usage
27
+
28
+ ```python
29
+ from transformers import AutoTokenizer, AutoModelForCausalLM
30
+ import torch
31
+
32
+ model = AutoModelForCausalLM.from_pretrained(
33
+ "LewinRobin/Medgemma_ROCOv2_Standalone", torch_dtype=torch.bfloat16, device_map="auto"
34
+ )
35
+ tokenizer = AutoTokenizer.from_pretrained("LewinRobin/Medgemma_ROCOv2_Standalone")
36
+
37
+ messages = [
38
+ {"role": "system", "content": "You are a highly experienced radiologist. Given a radiology image identifier and its associated UMLS medical concepts, write an accurate and concise radiology report caption."},
39
+ {"role": "user", "content": "Image ID: ROCOv2_2023_train_000001
40
+ Medical Concepts (UMLS CUIs): C0040405
41
+ Write the radiology report caption for this image."}
42
+ ]
43
+ text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
44
+ inputs = tokenizer(text, return_tensors="pt", return_token_type_ids=True).to(model.device)
45
+ out = model.generate(**inputs, max_new_tokens=128)
46
+ print(tokenizer.decode(out[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True))
47
+ ```
48
+
49
+ ## Training Details
50
+ - Base model : google/medgemma-4b-it
51
+ - Dataset : StanfordAIMI/rocov2 (~60 k samples)
52
+ - Method : QLoRA (merged) — 4-bit NF4, r=64, alpha=128
53
+ - Hardware : NVIDIA H100 80 GB
54
+ - Adapter source : [LewinRobin/Medgemma_Rocov2](https://huggingface.co/LewinRobin/Medgemma_Rocov2)
chat_template.jinja ADDED
@@ -0,0 +1,47 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {{ bos_token }}
2
+ {%- if messages[0]['role'] == 'system' -%}
3
+ {%- if messages[0]['content'] is string -%}
4
+ {%- set first_user_prefix = messages[0]['content'] + '
5
+
6
+ ' -%}
7
+ {%- else -%}
8
+ {%- set first_user_prefix = messages[0]['content'][0]['text'] + '
9
+
10
+ ' -%}
11
+ {%- endif -%}
12
+ {%- set loop_messages = messages[1:] -%}
13
+ {%- else -%}
14
+ {%- set first_user_prefix = "" -%}
15
+ {%- set loop_messages = messages -%}
16
+ {%- endif -%}
17
+ {%- for message in loop_messages -%}
18
+ {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}
19
+ {{ raise_exception("Conversation roles must alternate user/assistant/user/assistant/...") }}
20
+ {%- endif -%}
21
+ {%- if (message['role'] == 'assistant') -%}
22
+ {%- set role = "model" -%}
23
+ {%- else -%}
24
+ {%- set role = message['role'] -%}
25
+ {%- endif -%}
26
+ {{ '<start_of_turn>' + role + '
27
+ ' + (first_user_prefix if loop.first else "") }}
28
+ {%- if message['content'] is string -%}
29
+ {{ message['content'] | trim }}
30
+ {%- elif message['content'] is iterable -%}
31
+ {%- for item in message['content'] -%}
32
+ {%- if item['type'] == 'image' -%}
33
+ {{ '<start_of_image>' }}
34
+ {%- elif item['type'] == 'text' -%}
35
+ {{ item['text'] | trim }}
36
+ {%- endif -%}
37
+ {%- endfor -%}
38
+ {%- else -%}
39
+ {{ raise_exception("Invalid content type") }}
40
+ {%- endif -%}
41
+ {{ '<end_of_turn>
42
+ ' }}
43
+ {%- endfor -%}
44
+ {%- if add_generation_prompt -%}
45
+ {{'<start_of_turn>model
46
+ '}}
47
+ {%- endif -%}
config.json ADDED
@@ -0,0 +1,108 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "architectures": [
3
+ "Gemma3ForConditionalGeneration"
4
+ ],
5
+ "boi_token_index": 255999,
6
+ "dtype": "bfloat16",
7
+ "eoi_token_index": 256000,
8
+ "eos_token_id": [
9
+ 1,
10
+ 106
11
+ ],
12
+ "image_token_index": 262144,
13
+ "initializer_range": 0.02,
14
+ "mm_tokens_per_image": 256,
15
+ "model_type": "gemma3",
16
+ "text_config": {
17
+ "_sliding_window_pattern": 6,
18
+ "attention_bias": false,
19
+ "attention_dropout": 0.0,
20
+ "attn_logit_softcapping": null,
21
+ "bos_token_id": 2,
22
+ "dtype": "bfloat16",
23
+ "eos_token_id": 1,
24
+ "final_logit_softcapping": null,
25
+ "head_dim": 256,
26
+ "hidden_activation": "gelu_pytorch_tanh",
27
+ "hidden_size": 2560,
28
+ "initializer_range": 0.02,
29
+ "intermediate_size": 10240,
30
+ "layer_types": [
31
+ "sliding_attention",
32
+ "sliding_attention",
33
+ "sliding_attention",
34
+ "sliding_attention",
35
+ "sliding_attention",
36
+ "full_attention",
37
+ "sliding_attention",
38
+ "sliding_attention",
39
+ "sliding_attention",
40
+ "sliding_attention",
41
+ "sliding_attention",
42
+ "full_attention",
43
+ "sliding_attention",
44
+ "sliding_attention",
45
+ "sliding_attention",
46
+ "sliding_attention",
47
+ "sliding_attention",
48
+ "full_attention",
49
+ "sliding_attention",
50
+ "sliding_attention",
51
+ "sliding_attention",
52
+ "sliding_attention",
53
+ "sliding_attention",
54
+ "full_attention",
55
+ "sliding_attention",
56
+ "sliding_attention",
57
+ "sliding_attention",
58
+ "sliding_attention",
59
+ "sliding_attention",
60
+ "full_attention",
61
+ "sliding_attention",
62
+ "sliding_attention",
63
+ "sliding_attention",
64
+ "sliding_attention"
65
+ ],
66
+ "max_position_embeddings": 131072,
67
+ "model_type": "gemma3_text",
68
+ "num_attention_heads": 8,
69
+ "num_hidden_layers": 34,
70
+ "num_key_value_heads": 4,
71
+ "pad_token_id": 0,
72
+ "query_pre_attn_scalar": 256,
73
+ "rms_norm_eps": 1e-06,
74
+ "rope_parameters": {
75
+ "full_attention": {
76
+ "factor": 8.0,
77
+ "rope_theta": 1000000,
78
+ "rope_type": "linear"
79
+ },
80
+ "sliding_attention": {
81
+ "rope_theta": 10000,
82
+ "rope_type": "default"
83
+ }
84
+ },
85
+ "sliding_window": 1024,
86
+ "tie_word_embeddings": true,
87
+ "use_bidirectional_attention": false,
88
+ "use_cache": true,
89
+ "vocab_size": 262208
90
+ },
91
+ "tie_word_embeddings": true,
92
+ "transformers_version": "5.3.0",
93
+ "vision_config": {
94
+ "attention_dropout": 0.0,
95
+ "dtype": "bfloat16",
96
+ "hidden_act": "gelu_pytorch_tanh",
97
+ "hidden_size": 1152,
98
+ "image_size": 896,
99
+ "intermediate_size": 4304,
100
+ "layer_norm_eps": 1e-06,
101
+ "model_type": "siglip_vision_model",
102
+ "num_attention_heads": 16,
103
+ "num_channels": 3,
104
+ "num_hidden_layers": 27,
105
+ "patch_size": 14,
106
+ "vision_use_head": false
107
+ }
108
+ }
generation_config.json ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_from_model_config": true,
3
+ "bos_token_id": 2,
4
+ "eos_token_id": [
5
+ 1,
6
+ 106
7
+ ],
8
+ "pad_token_id": 0,
9
+ "transformers_version": "5.3.0"
10
+ }
model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5d2a218934a56b405957524618cd687f5cf2d99e629433dc06346c7fa885e044
3
+ size 8600278008
tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:daab2354f8a74e70d70b4d1f804939b68a8c9624dd06cb7858e52dd8970e9726
3
+ size 33384567
tokenizer_config.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "backend": "tokenizers",
3
+ "boi_token": "<start_of_image>",
4
+ "bos_token": "<bos>",
5
+ "clean_up_tokenization_spaces": false,
6
+ "eoi_token": "<end_of_image>",
7
+ "eos_token": "<eos>",
8
+ "image_token": "<image_soft_token>",
9
+ "is_local": false,
10
+ "mask_token": "<mask>",
11
+ "model_max_length": 1000000000000000019884624838656,
12
+ "model_specific_special_tokens": {
13
+ "boi_token": "<start_of_image>",
14
+ "eoi_token": "<end_of_image>",
15
+ "image_token": "<image_soft_token>"
16
+ },
17
+ "pad_token": "<pad>",
18
+ "processor_class": "Gemma3Processor",
19
+ "sp_model_kwargs": null,
20
+ "spaces_between_special_tokens": false,
21
+ "tokenizer_class": "GemmaTokenizer",
22
+ "unk_token": "<unk>",
23
+ "use_default_system_prompt": false
24
+ }