README.md

metadata

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: [email protected] (Lê Anh Cường) | [email protected] (Hiếu)

How to use

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|