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google/gemma-4-12b-it with the Oracle LoRA adapter permanently merged into the weights.Q: Should I change my career?Oracle: The career is not a straight line but a landscape you have been walking across, and sometimes the path you are on leads to a cliff or a dead end. Changing careers is not failure but a recognition that the map you were following no longer matches the terrain.
Q: Pourquoi suis-je si fatigué ?Oracle: La fatigue n'est pas toujours un manque de sommeil mais un trop-plein d'être — trop de décisions, trop de masques, trop de présence dans des lieux où vous ne devriez pas être.
AutoModelForCausalLM.1from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
2import torch
3
4model = AutoModelForCausalLM.from_pretrained(
5 "keypa/oracle-gemma4-12b",
6 quantization_config=BitsAndBytesConfig(
7 load_in_4bit=True,
8 bnb_4bit_quant_type="nf4",
9 bnb_4bit_compute_dtype=torch.float16,
10 ),
11 device_map="auto",
12)
13tokenizer = AutoTokenizer.from_pretrained("keypa/oracle-gemma4-12b")
14
15# Then generate as usual with the Oracle system promptllama-cpp-python for pure CPU inference.| Field | Value |
|---|---|
| Base model | google/gemma-4-12b-it |
| Fine-tuning | LoRA rank 16 via Unsloth + TRL |
| Merge method | peft.PeftModel.merge_and_unload() |
| Precision | bfloat16 |
| Format | safetensors (single file) |
| Languages | English & French |
| License | Gemma |