opparco

from transformers import AutoModelForCausalLM, AutoTokenizer


tokenizer = AutoTokenizer.from_pretrained("matsuo-lab/weblab-10b")

dot = tokenizer.encode(".")
print(dot)
# [15]

nemureru = tokenizer.encode("眠れる")

opparco

#
filename = '../grammars/japanese.gbnf'

print(f"overwrite {filename}")
with open(filename, 'w', encoding='utf-8') as f:
    f.write("""#
root ::= char+ ([ \\t\\n] char+)*
char ::= [\u3000-\u303F\u3040-\u309F\u30A0-\u30FF\u4E00-\u9FFF\uFF21-\uFF3A\uFF41-\uFF5A\uFF10-\uFF19]""")

opparco

C:\pub\llama.cpp\build>.\bin\Release\main.exe -m C:\pub\llama\llama-2-7b-chat\ggml-model-q4_K_M.bin -c 2048 -p "translate in japanese: The pen is mightier than the sword."
main: build = 852 (294f424)
main: seed  = 1690113032
llama.cpp: loading model from C:\pub\llama\llama-2-7b-chat\ggml-model-q4_K_M.bin
llama_model_load_internal: format     = ggjt v3 (latest)
llama_model_load_internal: n_vocab    = 32000
llama_model_load_internal: n_ctx      = 2048
llama_model_load_internal: n_embd     = 4096
llama_model_load_internal: n_mult     = 256
llama_model_load_internal: n_head     = 32

opparco

template<typename Key, typename T, T value = T()> 
class defaultable_map : 
	public std::unordered_map<Key, T> 
{ 
public: 
	// inherit std::unordered_map constructors 
	using std::unordered_map<Key, T>::unordered_map; 
 
	T & operator[](const Key & key) 
	{ 

opparco

Here are a few Yuri couples from Madoka Magica, formatted using Markdown:

1. Madoka Kaname and Kyubey
   • Madoka's determination to become a Magical Girl and Kyubey's manipulation of her desires create a complex and often fraught relationship.
2. Homura Akemi and Madoka Kaname
   • Homura's fierce protectiveness of Madoka and her willingness to make sacrifices for her rival's happiness create a powerful and emotional bond.
3. Kyoko Sakura and Sayaka Nakamura
   • Kyoko's quiet strength and Sayaka's desire to save her friend create a touching and heartwarming relationship.
4. Mami Tomoe and Kyoko Sakura
   • Mami's mentorship of Kyoko and Kyoko's admiration for Mami's strength and leadership create a beautiful and supportive relationship.

opparco

diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py
index 3895a795..a5765c3a 100644
--- a/scripts/xyz_grid.py
+++ b/scripts/xyz_grid.py
@@ -36,11 +36,24 @@ def apply_field(field):
 
 
 def apply_prompt(p, x, xs):
-    if xs[0] not in p.prompt and xs[0] not in p.negative_prompt:
-        raise RuntimeError(f"Prompt S/R did not find {xs[0]} in prompt or negative prompt.")

opparco

import requests


def main():
    prompt = "((masterpiece)), ((best quality)), ((illustration)), nsfw, beautiful thicc cute victorian girl, loli face, Feminine, Anders Zorn, ((cleavage of huge breasts)), puffy nipple, :d, blouse, long skirt"
    negative_prompt = "[[octane]], [[nsfw]], low hand,low arms,hand,arms,fingers,legs, lower body,thighs, cropped, worst quality, low quality,quality"

    sampling_methods = [
        "Euler a",
        "Euler",

opparco

diff --git a/modules/ui.py b/modules/ui.py
index 5dce7f3..3a5cc55 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -775,7 +775,7 @@ def create_ui(wrap_gradio_gpu_call):
                 show_progress=False,
             )
 
-            txt2img_prompt.submit(**txt2img_args)
+            txt2img_prompt.submit(api_name='txt2img', **txt2img_args)

opparco

import argparse
import torch


def main():
    parser = argparse.ArgumentParser()

    parser.add_argument(
        "--ckpt0",
        type=str,

opparco

diff --git a/ldm/modules/attention.py b/ldm/modules/attention.py
index f4eff39..f90c6c4 100644
--- a/ldm/modules/attention.py
+++ b/ldm/modules/attention.py
@@ -174,23 +174,27 @@ class CrossAttention(nn.Module):
         context = default(context, x)
         k = self.to_k(context)
         v = self.to_v(context)
+        del context, x