Remove spell files

nvim/spell/ltex.dictionary.en-GB.txt

@@ -1,53 +0,0 @@
-Avé
-Sint-Pietersvliet
-Starcraft
-Locobot
-DQN-based
-overcomplete
-QuaRL
-DDPG
-DQN
-softmax
-logits
-distill
-action-probablities
-UMAP
-XS
-DoReFa
-DoReFa-Net
-dequantized
-Tarrasque
-Liefstein
-Juandissimo
-Philfather
-lich
-liches
-Archfey
-Feywild
-Bulette
-Domdidle
-Koryk
-Ctheah
-TODO
-artifacts
-stochasticity
-playthrough
-StateManager
-defult
-subclassing
-spacebar
-Latré
-requantizing
-rvalue
-POMDPs
-DQNs
-Lumentis
-Strahd
-Irismore
-Copperford
-underdark
-Violetton
-Rainbowsmith
-Whitestead
-artificing
-Dwarven

nvim/spell/ltex.disabledRules.en-GB.txt

@@ -1,2 +0,0 @@
-WHITESPACE_RULE
-PROFANITY

nvim/spell/ltex.hiddenFalsePositives.en-GB.txt

@@ -1,10 +0,0 @@
-{"rule":"MORFOLOGIK_RULE_EN_GB","sentence":"^\\QBecause of this, linear methods are usually used in combination with PTQ for network parameters and to (de-)quantize the network inputs and outputs, as in those cases it is important that the relative values behind these representations are accurately maintained.\\E$"}
-{"rule":"AFFORD_VBG","sentence":"^\\QInitial work in the area of applying knowledge distillation in order to train low-precision neural networks in a supervised learning setting was done by \\E(?:Dummy|Ina|Jimmy-)[0-9]+\\Q.\\E$"}
-{"rule":"PRP_VBG","sentence":"^\\QThere is an additional benefit to training the low-precision network based on a full-precision teacher network compared to training it directly using more traditional DRL algorithms, such as DQN or PPO.\\E$"}
-{"rule":"CD_NN","sentence":"^\\Q3 Linear 1 Compression Ratio Parameters Student XXS 16 16 16 32 47.1x 35 796 Student XS 16 16 16 64 27.6x 61 044 Student S 16 16 16 128 15.1x 111 540 Student M 16 32 32 256 4.0x 424 276 Student L 32 64 64 256 1.9x 882 084 Student XL 32 64 64 512 1x 1 686 180 Student XXL 64 64 64 1024 0.5x 3 335 364 Sizes for the students used in our policy distillation experiments on the Atari Breakout environment.\\E$"}
-{"rule":"MORFOLOGIK_RULE_EN_GB","sentence":"^\\QNetwork Conv.\\E$"}
-{"rule":"MORFOLOGIK_RULE_EN_GB","sentence":"^\\Q1 Conv.\\E$"}
-{"rule":"MORFOLOGIK_RULE_EN_GB","sentence":"^\\Q2 Conv.\\E$"}
-{"rule":"ALLOW_TO","sentence":"^\\QA footnote says that in theory certain intelligent monstrosities could also train to become more powerful and throw off the bindings of age.\\E$"}
-{"rule":"MORFOLOGIK_RULE_EN_GB","sentence":"^\\QA quest: Book with golden hard-cover, located in a tower between Pan's village and Weathar.\\E$"}
-{"rule":"EN_COMPOUNDS","sentence":"^\\Q\\E(?:Dummy|Ina|Jimmy-)[0-9]+\\Q take this approach for a multi-task policy distillation, where a single agent is trained based on several teachers that are each specialized in a single task, with the goal of training a single student that is able to perform all tasks.\\E$"}