README.md

metadata

language:
  - vi
  - en
tags:
  - translation
  - pytorch
  - custom-architecture
pipeline_tag: text-generation
base_model:
  - FacebookAI/xlm-roberta-large

DLM Vi2En

This is a Vietnamese to English translation model based on the DLM architecture.

Base model is: "FacebookAI/xlm-roberta-large"

Requirements

Please ensure you have the following library versions installed:

pip install torch>=2.9.1 transformers>=4.57.3

Inference

Below is the Python code to run the model. It automatically utilizes the GPU if available and loads the model from the local cache after the first run.

import torch
from transformers import AutoTokenizer, AutoModel

# 1. Configuration
repo_id = "myduy/dlm-vi2en-checkpoint-90000"
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")

# 2. Load Model & Tokenizer
# trust_remote_code=True is required for custom architectures
tokenizer = AutoTokenizer.from_pretrained(repo_id, trust_remote_code=True)
model = AutoModel.from_pretrained(repo_id, trust_remote_code=True).to(device)
model.eval()

# 3. Prepare Input
text = "cậu có muốn đến nghe không?"
inputs = tokenizer(text, return_tensors="pt").to(device)

# 4. Generate
with torch.no_grad():
    output_tokens = model.generate(
        inputs.input_ids, 
        max_iterations=50, 
        temperature=1.0, 
        strategy="reparam-uncond-deterministic-cosine"
    )

# 5. Decode Output
output_text = tokenizer.batch_decode(output_tokens, skip_special_tokens=True)[0]

print(f"Input: {text}")
print(f"Output: {output_text}")