This repository highlights the outcome of an experimental merging algorithm that combined the weights of two distinct language models through the application of the add difference technique. The process of weight merging is an innovative approach that enables the integration of knowledge from multiple models, culminating in the development of a more dynamic and advanced language model.

  Proto-Synthia showcases an achievement in optimization within a mere 10 minutes, thereby, in many cases, obviating the need for the conventional time-intensive training process. 
{"license": "mit"}
transformers pytorch safetensors gpt2 text-generation license:mit autotrain_compatible endpoints_compatible has_space text-generation-inference region:us
TAGS
#transformers #pytorch #safetensors #gpt2 #text-generation #license-mit #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 

This repository highlights the outcome of an experimental merging algorithm that combined the weights of two distinct language models through the application of the add difference technique. The process of weight merging is an innovative approach that enables the integration of knowledge from multiple models, culminating in the development of a more dynamic and advanced language model.

  Proto-Synthia showcases an achievement in optimization within a mere 10 minutes, thereby, in many cases, obviating the need for the conventional time-intensive training process. 
TAGS
#transformers #pytorch #safetensors #gpt2 #text-generation #license-mit #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
