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KoboldAI-Client
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Merge branch 'main' into merge

This commit is contained in:
vfbd 2022-09-26 16:10:10 -04:00
parent ce692c7ebf 685ec3237b
commit 79ae0f17ec
4 changed files with 47 additions and 50 deletions
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33
aiserver.py
View File

@ -2491,15 +2491,14 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal
if(os.path.isdir(vars.custmodpth)): if(os.path.isdir(vars.custmodpth)):
try: try:
tokenizer = AutoTokenizer.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache") tokenizer = AutoTokenizer.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache")
except Exception as e:
pass
try:
tokenizer = AutoTokenizer.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache", use_fast=False)
except Exception as e: except Exception as e:
try: try:
tokenizer = GPT2TokenizerFast.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache") tokenizer = AutoTokenizer.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache", use_fast=False)
except Exception as e: except Exception as e:
tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache") try:
tokenizer = GPT2TokenizerFast.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache")
except Exception as e:
tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
try: try:
model = AutoModelForCausalLM.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache", **lowmem) model = AutoModelForCausalLM.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache", **lowmem)
except Exception as e: except Exception as e:
@ -2509,15 +2508,14 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal
elif(os.path.isdir("models/{}".format(vars.model.replace('/', '_')))): elif(os.path.isdir("models/{}".format(vars.model.replace('/', '_')))):
try: try:
tokenizer = AutoTokenizer.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache") tokenizer = AutoTokenizer.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache")
except Exception as e:
pass
try:
tokenizer = AutoTokenizer.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache", use_fast=False)
except Exception as e: except Exception as e:
try: try:
tokenizer = GPT2TokenizerFast.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache") tokenizer = AutoTokenizer.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache", use_fast=False)
except Exception as e: except Exception as e:
tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache") try:
tokenizer = GPT2TokenizerFast.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache")
except Exception as e:
tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
try: try:
model = AutoModelForCausalLM.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache", **lowmem) model = AutoModelForCausalLM.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache", **lowmem)
except Exception as e: except Exception as e:
@ -2540,15 +2538,14 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal
try: try:
tokenizer = AutoTokenizer.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache") tokenizer = AutoTokenizer.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache")
except Exception as e:
pass
try:
tokenizer = AutoTokenizer.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache", use_fast=False)
except Exception as e: except Exception as e:
try: try:
tokenizer = GPT2TokenizerFast.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache") tokenizer = AutoTokenizer.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache", use_fast=False)
except Exception as e: except Exception as e:
tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache") try:
tokenizer = GPT2TokenizerFast.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache")
except Exception as e:
tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
try: try:
model = AutoModelForCausalLM.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache", **lowmem) model = AutoModelForCausalLM.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache", **lowmem)
except Exception as e: except Exception as e:

29
static/application.js
View File

@ -1646,26 +1646,29 @@ function chunkOnBeforeInput(event) {
if(buildChunkSetFromNodeArray(getSelectedNodes()).size === 0) { if(buildChunkSetFromNodeArray(getSelectedNodes()).size === 0) {
var s = rangy.getSelection(); var s = rangy.getSelection();
var r = s.getRangeAt(0); var r = s.getRangeAt(0);
var rand = Math.random();
if(document.queryCommandSupported && document.execCommand && document.queryCommandSupported('insertHTML')) { if(document.queryCommandSupported && document.execCommand && document.queryCommandSupported('insertHTML')) {
document.execCommand('insertHTML', false, '<span id="_EDITOR_SENTINEL_">|</span>'); document.execCommand('insertHTML', false, '<span id="_EDITOR_SENTINEL_' + rand + '_">|</span>');
} else { } else {
var t = document.createTextNode('|'); var t = document.createTextNode('|');
var b = document.createElement('span'); var b = document.createElement('span');
b.id = "_EDITOR_SENTINEL_"; b.id = "_EDITOR_SENTINEL_" + rand + "_";
b.insertNode(t); b.insertNode(t);
r.insertNode(b); r.insertNode(b);
} }
var sentinel = document.getElementById("_EDITOR_SENTINEL_"); setTimeout(function() {
if(sentinel.nextSibling && sentinel.nextSibling.tagName === "CHUNK") { var sentinel = document.getElementById("_EDITOR_SENTINEL_" + rand + "_");
r.selectNodeContents(sentinel.nextSibling); if(sentinel.nextSibling && sentinel.nextSibling.tagName === "CHUNK") {
r.collapse(true); r.selectNodeContents(sentinel.nextSibling);
} else if(sentinel.previousSibling && sentinel.previousSibling.tagName === "CHUNK") { r.collapse(true);
r.selectNodeContents(sentinel.previousSibling); } else if(sentinel.previousSibling && sentinel.previousSibling.tagName === "CHUNK") {
r.collapse(false); r.selectNodeContents(sentinel.previousSibling);
} r.collapse(false);
s.removeAllRanges(); }
s.addRange(r); s.removeAllRanges();
sentinel.parentNode.removeChild(sentinel); s.addRange(r);
sentinel.parentNode.removeChild(sentinel);
}, 1);
} }
} }

2
templates/index.html
View File

@ -18,7 +18,7 @@
<script src="static/bootstrap.min.js"></script> <script src="static/bootstrap.min.js"></script>
<script src="static/bootstrap-toggle.min.js"></script> <script src="static/bootstrap-toggle.min.js"></script>
<script src="static/rangy-core.min.js"></script> <script src="static/rangy-core.min.js"></script>
<script src="static/application.js?ver=1.18.1e"></script> <script src="static/application.js?ver=1.18.1f"></script>
<script src="static/favicon.js"></script> <script src="static/favicon.js"></script>
</head> </head>
<body> <body>

33
tpu_mtj_backend.py
View File

@ -1352,15 +1352,14 @@ def load_model(path: str, driver_version="tpu_driver0.1_dev20210607", hf_checkpo
if(os.path.isdir(vars.custmodpth)): if(os.path.isdir(vars.custmodpth)):
try: try:
tokenizer = AutoTokenizer.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache") tokenizer = AutoTokenizer.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache")
except Exception as e:
pass
try:
tokenizer = AutoTokenizer.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache", use_fast=False)
except Exception as e: except Exception as e:
try: try:
tokenizer = GPT2TokenizerFast.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache") tokenizer = AutoTokenizer.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache", use_fast=False)
except Exception as e: except Exception as e:
tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache") try:
tokenizer = GPT2TokenizerFast.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache")
except Exception as e:
tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
try: try:
model = AutoModelForCausalLM.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache") model = AutoModelForCausalLM.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache")
except Exception as e: except Exception as e:
@ -1368,15 +1367,14 @@ def load_model(path: str, driver_version="tpu_driver0.1_dev20210607", hf_checkpo
elif(os.path.isdir("models/{}".format(vars.model.replace('/', '_')))): elif(os.path.isdir("models/{}".format(vars.model.replace('/', '_')))):
try: try:
tokenizer = AutoTokenizer.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache") tokenizer = AutoTokenizer.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache")
except Exception as e:
pass
try:
tokenizer = AutoTokenizer.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache", use_fast=False)
except Exception as e: except Exception as e:
try: try:
tokenizer = GPT2TokenizerFast.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache") tokenizer = AutoTokenizer.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache", use_fast=False)
except Exception as e: except Exception as e:
tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache") try:
tokenizer = GPT2TokenizerFast.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache")
except Exception as e:
tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
try: try:
model = AutoModelForCausalLM.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache") model = AutoModelForCausalLM.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache")
except Exception as e: except Exception as e:
@ -1384,15 +1382,14 @@ def load_model(path: str, driver_version="tpu_driver0.1_dev20210607", hf_checkpo
else: else:
try: try:
tokenizer = AutoTokenizer.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache") tokenizer = AutoTokenizer.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache")
except Exception as e:
pass
try:
tokenizer = AutoTokenizer.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache", use_fast=False)
except Exception as e: except Exception as e:
try: try:
tokenizer = GPT2TokenizerFast.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache") tokenizer = AutoTokenizer.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache", use_fast=False)
except Exception as e: except Exception as e:
tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache") try:
tokenizer = GPT2TokenizerFast.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache")
except Exception as e:
tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
try: try:
model = AutoModelForCausalLM.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache") model = AutoModelForCausalLM.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache")
except Exception as e: except Exception as e: