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import torch | |
import gradio as gr | |
import os | |
from transformers import ( | |
AutoModelForCausalLM, | |
AutoTokenizer, | |
TrainingArguments, | |
Trainer, | |
DataCollatorForLanguageModeling | |
) | |
# Force CPU mode | |
os.environ["CUDA_VISIBLE_DEVICES"] = "" | |
os.environ["BITSANDBYTES_NOWELCOME"] = "1" | |
def train(): | |
model = AutoModelForCausalLM.from_pretrained( | |
"microsoft/phi-2", | |
device_map="auto", | |
trust_remote_code=True, | |
load_in_4bit=False # Disable quantization | |
) | |
training_args = TrainingArguments( | |
output_dir="./results", | |
per_device_train_batch_size=2, | |
num_train_epochs=3, | |
use_cpu=True, # Explicit CPU usage | |
fp16=False, | |
bf16=False, | |
) | |
# Rest of training code... |