--- license: llama2 datasets: - nthngdy/oscar-mini - Tamnemtf/VietNamese_lang language: - vi pipeline_tag: text-generation --- ## Model Details - Model Name: llama-2-7b-vi-oscar_mini - Purpose: Mục đích để train con model này để phục vụ việc học và đề tài nckh. - Availability: The model checkpoint can be accessed on Hugging Face: Tamnemtf/llama-2-7b-vi-oscar_mini - Model trên được train dựa trên model gốc là ngoan/Llama-2-7b-vietnamese-20k ## How to Use ```python # Activate 4-bit precision base model loading use_4bit = True # Compute dtype for 4-bit base models bnb_4bit_compute_dtype = "float16" # Quantization type (fp4 or nf4) bnb_4bit_quant_type = "nf4" # Activate nested quantization for 4-bit base models (double quantization) use_nested_quant = False # Load the entire model on the GPU 0 device_map = {"": 0} ``` ```python compute_dtype = getattr(torch, bnb_4bit_compute_dtype) bnb_config = BitsAndBytesConfig( load_in_4bit=use_4bit, bnb_4bit_quant_type=bnb_4bit_quant_type, bnb_4bit_compute_dtype=compute_dtype, bnb_4bit_use_double_quant=use_nested_quant, ) ``` ```python model = AutoModelForCausalLM.from_pretrained( 'Tamnemtf/llama-2-7b-vi-oscar_mini', quantization_config=bnb_config, device_map=device_map ) model.config.use_cache = False model.config.pretraining_tp = 1 tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True) tokenizer.pad_token = tokenizer.eos_token tokenizer.padding_side = "right" # Fix weird overflow issue with fp16 training ``` ```python # Run text generation pipeline with our next model prompt = "Canh chua cá lau là món gì ?" pipe = pipeline(task="text-generation", model=model, tokenizer=tokenizer, max_length=200) result = pipe(f"[INST] {prompt} [/INST]") print(result[0]['generated_text']) ``` Để ưu tiên cho việc dễ dàng tiếp cận với các sinh viên dưới đây là mẫu ví dụ chạy thử model trên colab bằng T4 https://colab.research.google.com/drive/1ME_k-gUKSY2NbB7GQRk3sqz56CKsSV5C?usp=sharing ## Conntact nguyndantdm6@gmail.com