Initial commit.

main.py

@@ -0,0 +1,55 @@
+
+from transformers import AutoModelForCausalLM, AutoTokenizer, Trainer, TrainingArguments
+from typing import ClassVar
+from datasets import Dataset
+
+class AiTrainerParts:
+    DEFAULT_MODEL_NAME: ClassVar[str] = "deepseek-ai/DeepSeek-V3"
+
+    model: ClassVar[AutoModelForCausalLM]
+    model_name: ClassVar[str]
+    tokenizer: ClassVar[AutoTokenizer]
+    trainer: ClassVar[Trainer]
+
+    @classmethod
+    def make_default(cls):
+        return cls(cls.DEFAULT_MODEL_NAME)
+
+    def download_model_and_tokenizer(self):
+        self.model = AutoModelForCausalLM.from_pretrained(self.model_name)
+        self.tokenizer = AutoTokenizer.from_pretrained(self.model_name)
+
+    def save_model_and_tokenizer(self):
+        path = f"./pretrained_models/{self.model_name}"
+        self.model.save_pretrained(path)
+        self.tokenizer.save_pretrained(path)
+
+    @staticmethod
+    def tokenizer_preprocess_function(examples):
+        return tokenizer(examples["input"], truncation=True, padding="max_length", max_length=512)
+    def tokenize_training_data():
+        data = Dataset.from_dict({
+            "input": ["What is our company's mission?", "Who is the CEO?"],
+            "output": ["Our mission is to...", "The CEO is John Doe."]
+        })
+        tokenized_data = data.map(AiTrainerParts.tokenizer_preprocess_function, batched=True)
+        return tokenized_data
+
+    def fine_tune_model(self):
+        training_args = TrainingArguments(
+            output_dir="./deepseek-v3-finetuned",
+            per_device_train_batch_size=4,
+            num_train_epochs=3,
+            logging_dir="./logs",
+            save_steps=10_000,
+            save_total_limit=2,
+        )
+        trainer = Trainer(
+            model=self.model,
+            args=training_args,
+            train_dataset=self.training_data,
+        )
+        trainer.train()
+    def save_fine_tuned_model(self):
+        self.trainer.save_model("./deepseek-v3-finetuned")
+        self.tokenizer.save_pretrained("./deepseek-v3-finetuned")