OpenAI GPT-4 is said to be based on the Mixture of Experts architecture and has 1.76 trillion parameters. GPT-4is rumored to be based on eight models, each with 220 billion parameters, which are linked in the Mixture of Experts (MoE) architecture. The idea is nearly 30 years old and ha...
importgeopandas as gpdimportmatplotlib.pyplot as plt # Load the world shapefileworld = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres')) # Merge the world shapefile with the GPI data on the iso3c fieldforthe year2022merged = world.set_index('iso_a3').join(gpi_data.set_index(...
GPT-4 architecture, datasets, costs and more leaked https://medium.com/@itsrajayush2001/gpt-4-details-leaked-cb49411b9bdf https://gist.github.com/ykk648/cf7bf2b64897c29cfb0c67003bbbbea3
Prepare data Please download the annotation of the final mixture our instruction tuning datallava_v1_5_mix665k.json, and download the images from constituting datasets: COCO:train2017 GQA:images OCR-VQA:download script TextVQA:train_val_images VisualGenome:part1,part2 After downloading all of th...
“For most tasks we compare the per-token likelihood (to normalize for length), however on a small number of datasets (ARC, OpenBookQA, and RACE) we gain additional benefit as measured on the development set by normalizing by the unconditional probability of each completion ...”对于少数数据...
contexts = [] answers = [] # loop through the questions, run query for each question for question in questions: response = query_engine.query(question) contexts.append([x.node.get_content() for x in response.source_nodes]) answers.appen...
Note that if you apply Bessel's correction and divide by the number of instances - 1 rather than by the number of instance you will obtain, for small datasets, slightly different results (e.g. variance=[[0. , 2. , 1.] in the example). Either solutions are acceptable. 来自iPhone客户...
数据集地址:https://huggingface.co/datasets/griffin/chain_of_density 具体来说,他们将每个 token 的平均实体数量作为密度的代表,生成了一个初始的、实体稀少的摘要,然后在不增加总长度(总长度为 5 倍)的情况下,反复识别并融合前一个摘要中缺失的 1-3 个实体,每个摘要的实体与 token 比例都高于前一个摘要。
Specialized Datasets:After the initial pretraining phase, GPT-4 can be fine-tuned on more specific datasets to adapt to particular tasks or domains. This fine-tuningprocess makes the modelmore adept at tasks like translation, summarization, or code generation. ...