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fine_tune · nemotron_super_medical

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
from torch.utils.data import DataLoader

model = AutoModelForCausalLM.from_pretrained(
    "nvidia/nemotron-super-120b"
)
tokenizer = AutoTokenizer.from_pretrained(
    "nvidia/nemotron-super-120b"
)

train_data = torch.load("medical_corpus_sv.pt")
train_loader = DataLoader(train_data, batch_size=4)

optimizer = torch.optim.AdamW(model.parameters(), lr=2e-5)
epochs = 3

for epoch in range(epochs):
    for batch in train_loader:
        loss = model(**batch).loss
        loss.backward()
        optimizer.step()
        optimizer.zero_grad()

model.save_pretrained("nemotron-medical-sv")