model="openai:/gpt-3.5-turbo-16k", parameters={"temperature": 0.0}, aggregations=["...
torchrun --nnodes 1 --nproc_per_node 8 pretrain_hf.py \ --model_config_path ../config/config.json \ --tokenizer_name_or_path ../ckpt/Llama-2-13b-hf \ --per_device_train_batch_size 8 \ --do_train \ --seed 1234 \ --fp16 \ --num_train_epochs 1 \ --lr_scheduler_type ...
Post Processing(query后处理):当应用进行query查询的时候,我们使用相同的向量模型(embedding model)创建query的向量化表示,然后使用某种相似度搜索算法,在向量数据库中寻找top k个和该query的向量化表示相似的向量(vector embedding),并通过关联键得到与之对应的原始内容,这些原始内容就是向量数据库的搜索结果(query result...
我们可以暂时把模型看作一个函数 f(x),输入一个 Sequence Length × Dim 的矩阵,经过模型 f(x) 各种运算后会输出 Sequence Length × Vocabulary Size 大小的一个概率分布。有了概率分布就可以采样一个 Token ID(基于上下文最后一个 Token ID 的分布),这个 ID 也就是给定当前上下文(”我们喜欢Rust语言“)时...
Evaluation on Large Language Model (LLM) 作者在LLM环境中也对IceFormer进行了评估。具体来说,作者利用IceFormer来加速LLM中的提示处理过程。作者选择了Vicuna-7b-v1.5-16k,这是从LLaMA 2微调而来,并且是性能最佳的开放源码LLM之一,其上下文长度可达16K个标记,用于以下实验。关于包括IceFormer中的k -NNS中的k 选择...
Size of KV cache per token in bytes = 2 * (num_layers) * (num_heads * dim_head) * precision_in_bytes The first factor of 2 accounts for the K and V matrices. Commonly, the value of (num_heads * dim_head) is the same as the hidden_size (or dimension of the model, d_model...
model=AutoModel(model=model_dir,trust_remote_code=True,device="cuda:0")res=model.generate(input=f"{model.model_path}/example/en.mp3",cache={},language="zh",# "zh", "en", "yue", "ja", "ko", "nospeech"use_itn=False,batch_size=64, ) ...
Comparison of overall DTN consumption between LLM-Twin and FL-based DTN. Full size image Since the communication content of FL is always model parameters and state information, the communication cost will not be affected by time. The inter-twin communication of LLM-Twin requires searching for a ...
Size13B Training data20k GPT4 instructions ModelWizardML Size7B Training data70k instructions synthesized with ChatGPT/GPT-3 ModelOpenAssistant LLaMA Size13B, 30B Training data600k human interactions (OpenAssistant Conversations) LLaMA 基础模型
2.4.2. The influence from data on model capability Data influence encompasses two critical aspects: (1) Mix Ratio, which pertains to how data from different sources should be combined to create a fixed-size dataset within the constraints of a limited training budget, and (2) Data Curriculum,...