It isn’t just Morgan who’s cheered Endo on from the bullpen. “He was very scared in the beginning, so I took him for walks around the barn and then moved on to walks around the property,” said Morgan.īut thanks to his owner’s love and support, Endo quickly recovered and once again became the confident horse Morgan first fell in love with. “I just hoped he would be happy eating in his stall without pain, so we started there,” Morgan continued.Īnd so, Endo, the horse who once faced new challenges with courage and determination, became Endo the Blind.Īt first, losing his eyesight terrified him, and Morgan had to frequently coax him out of his stall. That was something that we just had to try and see how it went.” “I didn’t know how Endo would handle blindness.
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Within months, Endo’s left eye also began to give him problems and had to be removed as well, forcing him to learn how to navigate a world he could not see. Morgan worked together with Endo’s veterinarian to try and alleviate his pain by removing dust from his environment, rubbing prescription ointment on his eyes, and even taking him out for rides in the dark.Įndo’s pain unfortunately would not subside and when his right eye ruptured, Morgan made the incredibly difficult decision to have it removed. Moon blindness was historically named for its misperceived association with the moon’s phases, but it is now known that it has nothing to do with the moon and can instead recur over the course of weeks or months. The chronic, painful eye disease is characterised by repeated episodes of inflammation of the uveal tract (the middle layer) of the eye. The illness is one of the most common disorders of the equine eye and the leading cause of blindness in horses worldwide. “With each flare up, it also damaged his eyes.” “He continued to have flare ups and it got worse and worse as time went on,” said Morgan.
Morgan had her beloved gelding evaluated by a veterinarian, who diagnosed him with equine recurrent uveitis, also known as moon blindness or periodic ophthalmia. When he was eight years old, Morgan noticed Endo’s eyes tearing up and squinting often. “In the beginning, I didn’t know how to put a halter on him, and neither did he,” said Morgan. Advertisementsįrom their very first dressage and riding experiences together, to mastering trotting through some of the trickiest patterns and obstacles, there wasn’t a challenge their incredible bond couldn’t face.
Morgan and Endo grew up together, teaching one another everything there is to know about horseback riding. “He thinks he’s the greatest horse in the world and he wants everybody to know that.” “Endo has a big personality, that’s why I picked him out of all the babies my grandma had,” said Morgan. He had the most charisma and pranced around the other horses.”ĭespite being just a few months old, there was something very special about this intelligent and loving horse. “My grandma said I could have one of her horses, and I chose Endo. “I first met Endo on my grandma’s farm when my family and I moved up from California to Oregon,” said Morgan. When she was 13 years old, Morgan’s grandmother promised her she could have what almost every little girl dreams of: her very own horse.Īmong the herd, one fascinating foal caught her eye. (I believe this is good practice to have a general finetunig script for many different models, but it is just way to complicated for me right now and not a good starting point to understand how finetuning works.You may be wondering how the spectacular steed got his name.
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However, the code is very hard to understand for me, on the one hand because I have not used PyTorch Lightning yet and on the other hand because the code is not only for BART but for many different seq2seq models. They have a script for finetuning (finetune.py) as well as evaluation (run_eval.py). I also found some huggingface examples for seq2seq here. I tested the pre-trained bart-large-cnn model and got satisfying results. They also have pre-trained models for BART here. I realize there is this very nice library "huggingface transformers" that I guess most of you already know. Unfortunately, I am a beginner when it comes to PyTorch. I want to try BART for Multi-Document Summarization and for this I think the MultiNews dataset would be good. As the title suggests, I would like to finetune a pre-trained BART model on another dataset.
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