---
model-index:
- name: vietgpt/hoa-7b-250000
  results:
  - task:
      name: Word prediction
      type: text-generation
    dataset:
      type: vlsp-2023-vllm/lambada
      name: ViLambada
      split: test
    metrics:
    - type: Perplexity
      value: 6.950684856243125
  - task:
      name: Fewshot Translation
      type: translation
    dataset:
      type: vlsp-2023-vllm/en-to-vi-formal-informal-tranlations
      name: English to Vietnamese Formal/Informal translation
      split: test
    metrics:
    - type: SacreBLEU
      value: 26.3
datasets:
- vlsp-2023-vllm/vi_lambada
language:
- vi
- en
metrics:
- perplexity
library_name: transformers
pipeline_tag: text-generation
tags:
- llama2
- causal-lm
---

# Đà mã 2 (Llama2 architecture)

Dama2 is an autoregressive Large Language Model (LLM), based on Llama2's model architecture. 
Dama2 was trained on part of the Common Crawl dataset in Vietnamese and English.

Details will be available soon.

To contact us, mail to: leanhcuong@gmail.com (Lê Anh Cường) | hieunguyen1053@outlook.com (Hiếu)

### How to use 
```python
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("vietgpt/dama-2-7b")
model = AutoModelForCausalLM.from_pretrained("vietgpt/dama-2-7b", low_cpu_mem_usage=True)

device = torch.device("cuda" if torch.cuda.is_available() else "cpu") 
model.to(device)

prompt = "Địa chỉ trường Đại học Tôn Đức Thắng nằm ở số"
input_ids = tokenizer(prompt, return_tensors="pt")['input_ids'].to(device)

gen_tokens = model.generate(input_ids, max_length=max_length, repetition_penalty=1.1)

print(tokenizer.batch_decode(gen_tokens)[0])
```

```
{
  "results": {
    "lambada_vi": {
      "ppl": 17.662483545322115,
      "ppl_stderr": 0.46441057543941494,
      "acc": 0.34159672067148156,
      "acc_stderr": 0.004685401990271572
    }
  },
  "versions": {
    "lambada_vi": null
  },
  "config": {
    "model": "hf-causal",
    "model_args": "pretrained=vietgpt/dama-2-7b",
    "num_fewshot": 0,
    "batch_size": null,
    "batch_sizes": [],
    "device": "cuda:1",
    "no_cache": false,
    "limit": null,
    "bootstrap_iters": 100000,
    "description_dict": {}
  }
}
hf-causal (pretrained=vietgpt/dama-2-7b), limit: None, provide_description: False, num_fewshot: 0, batch_size: None
|   Task   |Version|Metric| Value |   |Stderr|
|----------|-------|------|------:|---|-----:|
|lambada_vi|       |ppl   |17.6625|±  |0.4644|
|          |       |acc   | 0.3416|±  |0.0047|
```