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--- |
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license: bigscience-bloom-rail-1.0 |
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language: |
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- vi |
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- en |
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library_name: transformers |
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pipeline_tag: text-generation |
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tags: |
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- bloom |
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- causal-lm |
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- pytorch |
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--- |
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# Hoa 7B (Bloom architecture) |
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Hoa is an autoregressive Large Language Model (LLM), based on Bloom's model architecture. |
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Hoa was trained on part of the Common Crawl dataset in Vietnamese and English. |
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Details will be available soon. |
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To contact us, mail to: leanhcuong@gmail.com (Lê Anh Cường) | hieunguyen1053@outlook.com (Hiếu) |
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### How to use |
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```python |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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tokenizer = AutoTokenizer.from_pretrained("vlsp-2023-vllm/hoa-7b") |
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model = AutoModelForCausalLM.from_pretrained("vlsp-2023-vllm/hoa-7b", low_cpu_mem_usage=True) |
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu") |
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model.to(device) |
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prompt = "Địa chỉ trường Đại học Tôn Đức Thắng nằm ở số" |
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input_ids = tokenizer(prompt, return_tensors="pt")['input_ids'].to(device) |
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gen_tokens = model.generate(input_ids, max_length=max_length, repetition_penalty=1.1) |
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print(tokenizer.batch_decode(gen_tokens)[0]) |
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``` |
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