Learn what translation, rotation, and reflection mean in math. Identify examples of these transformations and discover the key differences between...
def calculate_weight_diff(base_weight, chat_weight): return torch.abs(base_weight - chat_weight).mean().item() def calculate_layer_diffs(base_model, chat_model): layer_diffs = [] for base_layer, chat_layer in zip(base_model.model.layers, chat_model.model.layers): layer_diff = { '...
chat_weight): return torch.abs(base_weight - chat_weight).mean().item() def calculate_l...
它的底层模型建立在 metaLlama3.170B Instruct 上,并使用原始的 Llama chat 格式,确保了与现有工具和 pipeline 的兼容性。 这个模型横扫了 MMLU、MATH、IFeval、GSM8K,在每项基准测试上都超过了 GPT-4o,还击败了405B 的 Llama3.1。 凭借如此惊艳的效果,Reflection70B被冠以开源大模型新王。该模型更是由两位开发...
Explain the commutative property and the associative property in mathematics. What is closure property in math? What do the Symmetric Property and Transitive Property mean? What are the properties of a trapezium? What are vertical and horizontal reflections with functions? Which algebraic property or ...
Translation vs. Rotation vs. Reflection | Overview & Examples from Chapter 43 / Lesson 1 147K Learn what translation, rotation, and reflection mean in math. Identify examples of these transformations and discover the key differences between them. Related to this QuestionFor...
(base_weight - chat_weight).mean().item()def calculate_layer_diffs(base_model, chat_model):layer_diffs = []for base_layer, chat_layer in zip(base_model.model.layers, chat_model.model.layers):layer_diff = {'input_layernorm': calculate_weight_diff(base_layer.input_layernorm.weight, ...
(base_weight-chat_weight).mean().item()defcalculate_layer_diffs(base_model,chat_model):layer_diffs=[]forbase_layer,chat_layerinzip(base_model.model.layers,chat_model.model.layers):layer_diff={'input_layernorm':calculate_weight_diff(base_layer.input_layernorm.weight,chat_layer.input_layer...
A Java math framework based onmXparser librarycapabilities. You can calculate complex mathematical operations and functions with Java, just by using class-related fields, MXReflection reads values from the assigned fields and injects the results in the@Expressionannotated fields. ...
return torch.abs(base_weight - chat_weight).mean().item() def calculate_layer_diffs(base_model, chat_model): layer_diffs = [] for base_layer, chat_layer in zip(base_model.model.layers, chat_model.model.layers): layer_diff = { ...