input_columns: ["input_ids"] # "input_ids", "labels" , labels are used in instruction finetune. num_parallel_workers: 8 python_multiprocessing: False drop_remainder: True batch_size: 1 repeat: 1 numa_enable: False prefetch_size: 1 train_dataset_task: type: CausalLanguageModelDataset datas...
code llama就是在llama2模型【一文看懂llama2(原理,模型,训练)】的基础上,利用代码数据进行训练和微调,提高llama2在代码生成上的能力。 code llama提供了三种模型,每种模型包含7B,13B,34B三个尺寸,支持多种编程语言,如Python, C++, Java, PHP, Typescript (Javascript), C#, Bash等。 Code Llama,代码生成的基...
Code Llama - Python模型专门用于Python代码生成,也有7B、13B和34B参数的大小。它们旨在研究与通用代码生成模型相比,专门针对单一编程语言的模型的性能。从Llama 2模型初始化,并在Code Llama数据集的500B令牌上进行训练,Code Llama - Python模型进一步在一个以Python为主的数据集上使用100B令牌进行了专门化(第2.2节)...
Examples usingCodeLlama-7b-Instruct: torchrun --nproc_per_node 1 example_instructions.py \ --ckpt_dir CodeLlama-7b-Instruct/ \ --tokenizer_path CodeLlama-7b-Instruct/tokenizer.model \ --max_seq_len 512 --max_batch_size 4 Fine-tuned instruction-following models are: the Code Llama - Inst...
Pretrained infilling models are: the Code Llama models CodeLlama-7b and CodeLlama-13b and the Code Llama - Instruct models CodeLlama-7b-Instruct, CodeLlama-13b-Instruct. Fine-tuned Instruction Models Code Llama - Instruct models are fine-tuned to follow instructions. To get the expected features...
It is available in the base and instruction variants of the 7B and 13B models. Conversational Instructions CodeLlama's base model can be employed for both completion and infilling, as mentioned earlier. Additionally, there's an instruction fine-tuned model for use in conversational interfaces. ...
DARWIN 以开源的 LLaMA-7B 为基础,用开源科学FAIR数据集和科学文献,提取并整合结构化和非结构化的科学知识。用 100,000 多个指令数据点(instruction data points)对模型进行了微调(finetuning),生成了多样化的指令数据,并在微调过程中引入了科学指令生成(SIG)模型,实现了基于科学文本的指令自动生成。
It comes in three variants, engineered to cover a wide variety of applications: the foundational model (Code Llama), a Python specialized model (Code Llama Python), and an instruction-following model for understanding natural language instructions (Code Llama Instruct). All Code Lla...
It comes in three variants, engineered to cover a wide variety of applications: the foundational model (Code Llama), a Python specialized model (Code Llama Python), and an instruction-following model for understanding natural language instructions (Code Llama Instruct). All Code Llam...
DARWIN 以开源的 LLaMA-7B 为基础,用开源科学FAIR数据集和科学文献,提取并整合结构化和非结构化的科学知识。用 100,000 多个指令数据点(instruction data points)对模型进行了微调(finetuning),生成了多样化的指令数据,并在微调过程中引入了科学指令生成(SIG)模型,实现了基于科学文本的指令自动生成。