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| license: other |
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|  |
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| <h4 align="center"> |
| <p> |
| <b>English</b> | |
| <a href="https://huggingface.co/BAAI/Aquila2-34B/blob/main/README_zh.md">简体中文</a> | |
| <p> |
| </h4> |
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| We opensource our **Aquila2** series, now including **Aquila2**, the base language models, namely **Aquila2-7B** and **Aquila2-34B**, as well as **AquilaChat2**, the chat models, namely **AquilaChat2-7B** and **AquilaChat2-34B**, as well as the long-text chat models, namely **AquilaChat2-7B-16k** and **AquilaChat2-34B-16k** |
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| The additional details of the Aquila model will be presented in the official technical report. Please stay tuned for updates on official channels. |
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| ## Updates 2024.6.6 |
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| We have updated the basic language model **Aquila2-34B**, which has the following advantages compared to the previous model: |
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| * Replaced tokenizer with higher compression ratio: |
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| | Tokenizer | Size | Zh | En | Code | Math | Average | |
| |-----------|-------|--------------------------|--------|-------|-------|---------| |
| | Aquila2-original | 100k | **4.70** | 4.42 | 3.20 | 3.77 | 4.02 | |
| | Qwen1.5 | 151k | 4.27 | 4.51 | 3.62 | 3.35 | 3.94 | |
| | Llama3 | 128k | 3.45 | **4.61** | 3.77 | **3.88** | 3.93 | |
| | Aquila2-new | 143k | 4.60 | **4.61** | **3.78** | **3.88** | **4.22** | |
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| * The maximum processing length supported by the model has increased from 2048 to 8192 |
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| ## Quick Start Aquila2-34B |
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| ### 1. Inference |
| Aquila2-34B is a base model that can be used for continuation. |
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| ```python |
| import torch |
| from transformers import AutoModelForCausalLM, AutoTokenizer |
| from transformers import BitsAndBytesConfig |
| |
| device= "cuda:0" |
| |
| # Model Name |
| model_name = 'BAAI/Aquila2-34B' |
| |
| # load model and tokenizer |
| quantization_config=BitsAndBytesConfig( |
| load_in_4bit=True, |
| bnb_4bit_use_double_quant=True, |
| bnb_4bit_quant_type="nf4", |
| bnb_4bit_compute_dtype=torch.bfloat16, |
| ) |
| model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, trust_remote_code=True, |
| # quantization_config=quantization_config # Uncomment this one for 4-bit quantization |
| ) |
| |
| tokenizer = AutoTokenizer.from_pretrained(path, trust_remote_code=True) |
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| model.eval() |
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| model.to(device) |
| |
| # Example |
| text = "The meaning of life is" |
| tokens = tokenizer.encode_plus(text)['input_ids'] |
| tokens = torch.tensor(tokens)[None,].to(device) |
| |
| with torch.no_grad(): |
| out = model.generate(tokens, do_sample=False, max_length=128, eos_token_id=tokenizer.eos_token_id)[0] |
| out = tokenizer.decode(out.cpu().numpy().tolist()) |
| print(out) |
| ``` |
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|
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| ## License |
|
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| Aquila2 series open-source model is licensed under [ BAAI Aquila Model Licence Agreement](https://huggingface.co/BAAI/Aquila2-34B/blob/main/BAAI-Aquila-Model-License%20-Agreement.pdf) |
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