Nothing
## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(echo = TRUE, eval = FALSE)
## -----------------------------------------------------------------------------
# reticulate::py_install('ohmeow-blurr',pip = TRUE)
## -----------------------------------------------------------------------------
# library(fastai)
# library(magrittr)
# library(zeallot)
#
# cnndm_df = data.table::fread('https://raw.githubusercontent.com/ohmeow/blurr/master/nbs/cnndm_sample.csv')
## -----------------------------------------------------------------------------
# transformers = transformers()
#
# BartForConditionalGeneration = transformers$BartForConditionalGeneration
#
# pretrained_model_name = "facebook/bart-large-cnn"
# c(hf_arch, hf_config, hf_tokenizer, hf_model) %<-%
# get_hf_objects(pretrained_model_name,model_cls=BartForConditionalGeneration)
## -----------------------------------------------------------------------------
#
# before_batch_tfm = HF_SummarizationBeforeBatchTransform(hf_arch,
# hf_tokenizer, max_length=c(256, 130))
# blocks = list(HF_Text2TextBlock(before_batch_tfms=before_batch_tfm,
# input_return_type=HF_SummarizationInput), noop())
#
# dblock = DataBlock(blocks=blocks,
# get_x=ColReader('article'),
# get_y=ColReader('highlights'),
# splitter=RandomSplitter())
#
# dls = dblock %>% dataloaders(cnndm_df, bs=2)
#
# dls %>% one_batch()
#
## -----------------------------------------------------------------------------
# text_gen_kwargs = hf_config$task_specific_params['summarization'][[1]]
# text_gen_kwargs['max_length'] = 130L; text_gen_kwargs['min_length'] = 30L
#
# text_gen_kwargs
#
# model = HF_BaseModelWrapper(hf_model)
# model_cb = HF_SummarizationModelCallback(text_gen_kwargs=text_gen_kwargs)
#
# learn = Learner(dls,
# model,
# opt_func=partial(Adam),
# loss_func=CrossEntropyLossFlat(), #HF_PreCalculatedLoss()
# cbs=model_cb,
# splitter=partial(summarization_splitter, arch=hf_arch)) #.to_native_fp16() #.to_fp16()
#
# learn$create_opt()
# learn$freeze()
#
# learn %>% fit_one_cycle(1, lr_max=4e-5)
## -----------------------------------------------------------------------------
# test_article = c("About 10 men armed with pistols and small machine guns raided a casino in Switzerland
# and made off into France with several hundred thousand Swiss francs in the early hours
# of Sunday morning, police said. The men, dressed in black clothes and black ski masks,
# split into two groups during the raid on the Grand Casino Basel, Chief Inspector Peter
# Gill told CNN. One group tried to break into the casino's vault on the lower level
# but could not get in, but they did rob the cashier of the money that was not secured,
# he said. The second group of armed robbers entered the upper level where the roulette
# and blackjack tables are located and robbed the cashier there, he said. As the thieves
# were leaving the casino, a woman driving by and unaware of what was occurring unknowingly
# blocked the armed robbers' vehicles. A gunman pulled the woman from her vehicle, beat
# her, and took off for the French border. The other gunmen followed into France, which
# is only about 100 meters (yards) from the casino, Gill said. There were about 600 people
# in the casino at the time of the robbery. There were no serious injuries, although one
# guest on the Casino floor was kicked in the head by one of the robbers when he moved,
# the police officer said. Swiss authorities are working closely with French authorities,
# Gill said. The robbers spoke French and drove vehicles with French lRicense plates.
# CNN's Andreena Narayan contributed to this report.")
## -----------------------------------------------------------------------------
# outputs = learn$blurr_summarize(test_article, num_return_sequences=3L)
# cat(outputs)
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.