transformers pytorch bloom text-generation causal-lm vi en license:bigscience-bloom-rail-1.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: bigscience-bloom-rail-1.0
language:
- vi
- en
library_name: transformers
pipeline_tag: text-generation
tags:
- bloom
- causal-lm
- pytorch
---

# Hoa 7B (Bloom architecture)

Hoa is an autoregressive Large Language Model (LLM), based on Bloom's model architecture. 
Hoa 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("vlsp-2023-vllm/hoa-7b")
model = AutoModelForCausalLM.from_pretrained("vlsp-2023-vllm/hoa-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])
```

