Delete train.py

train.py

@@ -1,40 +0,0 @@
-from transformers import AutoModelForCausalLM, AutoTokenizer, Trainer, TrainingArguments
-from datasets import load_dataset
-
-# Load the model and tokenizer
-model = AutoModelForCausalLM.from_pretrained("Saad381/SpectraGen")
-tokenizer = AutoTokenizer.from_pretrained("Saad381/SpectraGen")
-
-# Load your dataset (CSV file assumed here)
-dataset = load_dataset('csv', data_files='dataset.csv')
-
-# Tokenize your dataset
-def tokenize_function(examples):
-    return tokenizer(examples["text"], padding="max_length", truncation=True)
-
-tokenized_datasets = dataset.map(tokenize_function, batched=True)
-
-# Define training arguments
-training_args = TrainingArguments(
-    output_dir='./results',          # output directory
-    evaluation_strategy="epoch",     # evaluate at end of each epoch
-    per_device_train_batch_size=8,   # batch size
-    num_train_epochs=3,              # number of training epochs
-    save_steps=10_000,               # steps to save checkpoint
-    save_total_limit=2,              # limit the total amount of checkpoints
-)
-
-# Initialize the Trainer
-trainer = Trainer(
-    model=model,
-    args=training_args,
-    train_dataset=tokenized_datasets["train"],
-    eval_dataset=tokenized_datasets["test"]
-)
-
-# Train the model
-trainer.train()
-
-# Save the model
-model.save_pretrained('./trained_model')
-tokenizer.save_pretrained('./trained_model')