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https://github.com/oobabooga/text-generation-webui.git
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Add HTML support for gpt4chan
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154
html_generator.py
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154
html_generator.py
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'''
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This is a library for formatting gpt4chan outputs as nice HTML.
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'''
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import re
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def process_post(post, c):
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t = post.split('\n')
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number = t[0].split(' ')[1]
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if len(t) > 1:
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src = '\n'.join(t[1:])
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else:
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src = ''
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src = re.sub('>', '>', src)
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src = re.sub('(>>[0-9]*)', '<span class="quote">\\1</span>', src)
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src = re.sub('\n', '<br>\n', src)
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src = f'<blockquote class="message">{src}\n'
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src = f'<span class="name">Anonymous </span> <span class="number">No.{number}</span>\n{src}'
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return src
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def generate_html(f):
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css = """
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#container {
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background-color: #eef2ff;
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padding: 17px;
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}
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.reply {
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background-color: rgb(214, 218, 240);
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border-bottom-color: rgb(183, 197, 217);
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border-bottom-style: solid;
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border-bottom-width: 1px;
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border-image-outset: 0;
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border-image-repeat: stretch;
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border-image-slice: 100%;
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border-image-source: none;
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border-image-width: 1;
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border-left-color: rgb(0, 0, 0);
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border-left-style: none;
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border-left-width: 0px;
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border-right-color: rgb(183, 197, 217);
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border-right-style: solid;
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border-right-width: 1px;
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border-top-color: rgb(0, 0, 0);
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border-top-style: none;
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border-top-width: 0px;
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color: rgb(0, 0, 0);
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display: table;
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font-family: arial, helvetica, sans-serif;
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font-size: 13.3333px;
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margin-bottom: 4px;
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margin-left: 0px;
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margin-right: 0px;
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margin-top: 4px;
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overflow-x: hidden;
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overflow-y: hidden;
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padding-bottom: 2px;
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padding-left: 2px;
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padding-right: 2px;
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padding-top: 2px;
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}
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.number {
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color: rgb(0, 0, 0);
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font-family: arial, helvetica, sans-serif;
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font-size: 13.3333px;
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width: 342.65px;
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}
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.op {
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color: rgb(0, 0, 0);
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font-family: arial, helvetica, sans-serif;
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font-size: 13.3333px;
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margin-bottom: 8px;
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margin-left: 0px;
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margin-right: 0px;
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margin-top: 4px;
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overflow-x: hidden;
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overflow-y: hidden;
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}
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.op blockquote {
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margin-left:7px;
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}
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.name {
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color: rgb(17, 119, 67);
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font-family: arial, helvetica, sans-serif;
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font-size: 13.3333px;
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font-weight: 700;
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margin-left: 7px;
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}
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.quote {
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color: rgb(221, 0, 0);
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font-family: arial, helvetica, sans-serif;
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font-size: 13.3333px;
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text-decoration-color: rgb(221, 0, 0);
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text-decoration-line: underline;
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text-decoration-style: solid;
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text-decoration-thickness: auto;
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}
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.greentext {
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color: rgb(120, 153, 34);
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font-family: arial, helvetica, sans-serif;
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font-size: 13.3333px;
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}
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blockquote {
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margin-block-start: 1em;
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margin-block-end: 1em;
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margin-inline-start: 40px;
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margin-inline-end: 40px;
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}
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"""
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posts = []
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post = ''
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c = -2
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for line in f.splitlines():
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line += "\n"
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if line == '-----\n':
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continue
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elif line.startswith('--- '):
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c += 1
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if post != '':
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src = process_post(post, c)
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posts.append(src)
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post = line
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else:
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post += line
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if post != '':
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src = process_post(post, c)
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posts.append(src)
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for i in range(len(posts)):
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if i == 0:
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posts[i] = f'<div class="op">{posts[i]}</div>\n'
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else:
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posts[i] = f'<div class="reply">{posts[i]}</div>\n'
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output = ''
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output += f'<style>{css}</style><div id="container">'
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for post in posts:
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output += post
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output += '</div>'
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output = output.split('\n')
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for i in range(len(output)):
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output[i] = re.sub('^(>[^\n]*(<br>|</div>))', '<span class="greentext">\\1</span>\n', output[i])
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output = '\n'.join(output)
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return output
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22
server.py
22
server.py
@ -7,15 +7,19 @@ import torch
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import argparse
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import argparse
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import gradio as gr
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import gradio as gr
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import transformers
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import transformers
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from html_generator import *
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from transformers import AutoTokenizer
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from transformers import AutoTokenizer
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from transformers import GPTJForCausalLM, AutoModelForCausalLM, AutoModelForSeq2SeqLM, OPTForCausalLM, T5Tokenizer, T5ForConditionalGeneration, GPTJModel, AutoModel
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from transformers import GPTJForCausalLM, AutoModelForCausalLM, AutoModelForSeq2SeqLM, OPTForCausalLM, T5Tokenizer, T5ForConditionalGeneration, GPTJModel, AutoModel
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parser = argparse.ArgumentParser()
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parser = argparse.ArgumentParser()
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parser.add_argument('--model', type=str, help='Name of the model to load by default.')
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parser.add_argument('--model', type=str, help='Name of the model to load by default.')
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parser.add_argument('--notebook', action='store_true', help='Launch the webui in notebook mode, where the output is written to the same text box as the input.')
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parser.add_argument('--notebook', action='store_true', help='Launch the webui in notebook mode, where the output is written to the same text box as the input.')
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args = parser.parse_args()
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args = parser.parse_args()
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loaded_preset = None
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loaded_preset = None
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available_models = sorted(set(map(lambda x : x.split('/')[-1].replace('.pt', ''), glob.glob("models/*[!\.][!t][!x][!t]")+ glob.glob("torch-dumps/*[!\.][!t][!x][!t]"))))
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available_models = sorted(set(map(lambda x : x.split('/')[-1].replace('.pt', ''), glob.glob("models/*")+ glob.glob("torch-dumps/*"))))
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available_models = [item for item in available_models if not item.endswith('.txt')]
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#available_models = sorted(set(map(lambda x : x.split('/')[-1].replace('.pt', ''), glob.glob("models/*[!\.][!t][!x][!t]")+ glob.glob("torch-dumps/*[!\.][!t][!x][!t]"))))
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def load_model(model_name):
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def load_model(model_name):
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print(f"Loading {model_name}...")
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print(f"Loading {model_name}...")
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@ -75,15 +79,17 @@ def generate_reply(question, temperature, max_length, inference_settings, select
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input_ids = tokenizer.encode(str(input_text), return_tensors='pt').cuda()
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input_ids = tokenizer.encode(str(input_text), return_tensors='pt').cuda()
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output = eval(f"model.generate(input_ids, {preset}).cuda()")
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output = eval(f"model.generate(input_ids, {preset}).cuda()")
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reply = tokenizer.decode(output[0], skip_special_tokens=True)
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reply = tokenizer.decode(output[0], skip_special_tokens=True)
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if model_name.startswith('gpt4chan'):
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if model_name.startswith('gpt4chan'):
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reply = fix_gpt4chan(reply)
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reply = fix_gpt4chan(reply)
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if model_name.lower().startswith('galactica'):
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if model_name.lower().startswith('galactica'):
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return reply, reply
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return reply, reply, 'Only applicable for gpt4chan.'
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elif model_name.lower().startswith('gpt4chan'):
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return reply, 'Only applicable for galactica models.', generate_html(reply)
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else:
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else:
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return reply, 'Only applicable for galactica models.'
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return reply, 'Only applicable for galactica models.', 'Only applicable for gpt4chan.'
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# Choosing the default model
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# Choosing the default model
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if args.model is not None:
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if args.model is not None:
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textbox = gr.Textbox(value=default_text, lines=23)
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textbox = gr.Textbox(value=default_text, lines=23)
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with gr.Tab('Markdown'):
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with gr.Tab('Markdown'):
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markdown = gr.Markdown()
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markdown = gr.Markdown()
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with gr.Tab('HTML'):
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html = gr.HTML()
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btn = gr.Button("Generate")
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btn = gr.Button("Generate")
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with gr.Row():
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with gr.Row():
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@ -131,7 +139,7 @@ if args.notebook:
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preset_menu = gr.Dropdown(choices=list(map(lambda x : x.split('/')[-1].split('.')[0], glob.glob("presets/*.txt"))), value="Default", label='Preset')
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preset_menu = gr.Dropdown(choices=list(map(lambda x : x.split('/')[-1].split('.')[0], glob.glob("presets/*.txt"))), value="Default", label='Preset')
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model_menu = gr.Dropdown(choices=available_models, value=model_name, label='Model')
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model_menu = gr.Dropdown(choices=available_models, value=model_name, label='Model')
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btn.click(generate_reply, [textbox, temp_slider, length_slider, preset_menu, model_menu], [textbox, markdown], show_progress=False)
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btn.click(generate_reply, [textbox, temp_slider, length_slider, preset_menu, model_menu], [textbox, markdown, html], show_progress=False)
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else:
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else:
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with gr.Blocks() as interface:
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with gr.Blocks() as interface:
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gr.Markdown(
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gr.Markdown(
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@ -154,7 +162,9 @@ else:
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output_textbox = gr.Textbox(value=default_text, lines=15, label='Output')
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output_textbox = gr.Textbox(value=default_text, lines=15, label='Output')
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with gr.Tab('Markdown'):
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with gr.Tab('Markdown'):
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markdown = gr.Markdown()
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markdown = gr.Markdown()
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with gr.Tab('HTML'):
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html = gr.HTML()
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btn.click(generate_reply, [textbox, temp_slider, length_slider, preset_menu, model_menu], [output_textbox, markdown], show_progress=True)
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btn.click(generate_reply, [textbox, temp_slider, length_slider, preset_menu, model_menu], [output_textbox, markdown, html], show_progress=True)
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interface.launch(share=False, server_name="0.0.0.0")
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interface.launch(share=False, server_name="0.0.0.0")
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