需求Demand任务Task系列Series模型Model参数Parameter额外Extra 通用General AGI模型 姜子牙 Ziya LLaMA 13B English&Chinese 模型信息 Model Information 继续预训练 Continual pretraining 原始数据包含英文和中文,其中英文数据来自openwebtext、Books、Wikipedia和Code,中文数据来自清洗后的悟道数据集、自建的中文数据集。在对原...
base-110M parameters) [Devlin et al., 2018]. BERT is the foundational model for many early PLMs, including FinBERT. Since OpenAI shifted from open-source to closed-source LLMs, the trend across LLM research is a reduction in
The 1.7B parameter model uses a more traditional architecture. For all three models we use embedding tying and a context length of 2048 tokens. This context length can be further extended with some long context fine-tuning. The detailed architecture specifications for each model size are as ...
“When training a 65B-parameter model, our code processes around 380 tokens/sec/GPU on 2048 A100 GPU with 80GB of RAM. This means that training over our dataset containing 1.4T tokens takes approximately 21 days.”— from [1] Given the modifications that LLaMA adopts to improve training effi...
The problem comes when you try to run models, particularly larger ones, with 16-bit tensors on a single chip. At two bytes per parameter, a model like Llama-3-70B requires at least 140GB of very fast memory, and that's not including other overheads, such as the key-value cache. ...
In this paper, we present our solutions to train an LLM at the 100B-parameter scale using a growth strategy inspired by our previous research [78]. “Growth” means that the number of parameters is not fixed, but expands from small to large along the training progresses. Figure 1 illustrat...
65 billion parameter models that revert back to smaller but much larger token size models. And so there is no doubt that language is model one for all enterprises. And there’s a good reason for that. If you actually look at what happens with every corporation, data at rest, despite the...
While LLMs will continue to advance, ethical AI and safety will become increasingly important. with firms such as Anthropic developing reliable and interpretable AI systems. The trend towards open-source models and strategic collaborations, as seen with Meta and Amazon, will foster broader innovation...
The primary advantage of these parameter-efficient methods like LoRA lies in more efficient model deployment, particularly when managing multiple specialized models. This is increasingly relevant as the trend moves towards developing an array of specialized LLMs tailored for various tasks. ...
GPT-4, an LLM, dwarfs all predecessors in terms of its parameter count. Examples of LLMs Here is a list of the top 10 LLMs on the market, listed in alphabetical order based on internet research: Bidirectional Encoder Representations from Transformers, commonly referred to as Bert. Claude. ...