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1
2merge_method: linear
3parameters:
4 normalize: true
5dtype: bfloat16
6models:
7 - model: tepirale/gemma-4-12B-coder-fable5-composer2.5-v1-safetensors-yuxinlu1
8 parameters:
9 weight: 0.4
10 - model: tepirale/gemma-4-12B-agentic-fable5-composer2.5-v2-3.5x-tau2-safetensors-yuxinlu1
11 parameters:
12 weight: 0.4
13 - model: google/gemma-4-12B-it
14 parameters:
15 weight: 0.2
161import torch
2from transformers import AutoProcessor, AutoModelForMultimodalLM, AutoModelForCausalLM
3
4
5MODEL_ID_HUB = "tepirale/gemma-4-12B-merge-coder40-agentic40-it20"
6MA= "tepirale/gemma-4-12B-agentic-fable5-composer2.5-v2-3.5x-tau2-assistant-safetensors-yuxinlu1"
7
8
9model = AutoModelForMultimodalLM.from_pretrained(
10 MODEL_ID_HUB,
11 dtype="auto",
12 device_map="auto",
13 # local_files_only=True
14)
15
16assistant_model = AutoModelForCausalLM.from_pretrained(MA,
17 dtype=torch.bfloat16,
18 device_map="auto"
19 )
20
21processor = AutoProcessor.from_pretrained(MODEL_ID_HUB)
22
23
24# Prompt - add image before text
25messages = [
26 {
27 "role": "user", "content": [
28 {"type": "image", "url": "https://raw.githubusercontent.com/google-gemma/cookbook/refs/heads/main/apps/sample-data/GoldenGate.png"},
29 {"type": "text", "text": "What is shown in this image?"}
30 ]
31 }
32]
33
34# Process input
35inputs = processor.apply_chat_template(
36 messages,
37 tokenize=True,
38 return_dict=True,
39 return_tensors="pt",
40 add_generation_prompt=True,
41 enable_thinking=True
42).to(model.device)
43input_len = inputs["input_ids"].shape[-1]
44
45# Generate output
46outputs = model.generate(**inputs, max_new_tokens=3512, assistant_model=assistant_model)
47response = processor.decode(outputs[0][input_len:], skip_special_tokens=False)
48
49# Parse output
50processor.parse_response(response)
51