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KoboldAI-Client
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Merge pull request #216 from VE-FORBRYDERNE/merge 

Merge main into united
This commit is contained in:
henk717 2022-09-26 22:11:44 +02:00 committed by GitHub
parent ce692c7ebf 79ae0f17ec
commit 7f5ba8a678
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GPG Key ID: 4AEE18F83AFDEB23
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)):
try:
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:
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:
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:
model = AutoModelForCausalLM.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache", **lowmem)
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('/', '_')))):
try:
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:
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:
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:
model = AutoModelForCausalLM.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache", **lowmem)
except Exception as e:
@ -2540,15 +2538,14 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal
try:
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:
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:
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:
model = AutoModelForCausalLM.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache", **lowmem)
except Exception as e:

29
static/application.js
View File

@ -1646,26 +1646,29 @@ function chunkOnBeforeInput(event) {
if(buildChunkSetFromNodeArray(getSelectedNodes()).size === 0) {
var s = rangy.getSelection();
var r = s.getRangeAt(0);
var rand = Math.random();
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 {
var t = document.createTextNode('|');
var b = document.createElement('span');
b.id = "_EDITOR_SENTINEL_";
b.id = "_EDITOR_SENTINEL_" + rand + "_";
b.insertNode(t);
r.insertNode(b);
}
var sentinel = document.getElementById("_EDITOR_SENTINEL_");
if(sentinel.nextSibling && sentinel.nextSibling.tagName === "CHUNK") {
r.selectNodeContents(sentinel.nextSibling);
r.collapse(true);
} else if(sentinel.previousSibling && sentinel.previousSibling.tagName === "CHUNK") {
r.selectNodeContents(sentinel.previousSibling);
r.collapse(false);
}
s.removeAllRanges();
s.addRange(r);
sentinel.parentNode.removeChild(sentinel);
setTimeout(function() {
var sentinel = document.getElementById("_EDITOR_SENTINEL_" + rand + "_");
if(sentinel.nextSibling && sentinel.nextSibling.tagName === "CHUNK") {
r.selectNodeContents(sentinel.nextSibling);
r.collapse(true);
} else if(sentinel.previousSibling && sentinel.previousSibling.tagName === "CHUNK") {
r.selectNodeContents(sentinel.previousSibling);
r.collapse(false);
}
s.removeAllRanges();
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-toggle.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>
</head>
<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)):
try:
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:
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:
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:
model = AutoModelForCausalLM.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache")
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('/', '_')))):
try:
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:
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:
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:
model = AutoModelForCausalLM.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache")
except Exception as e:
@ -1384,15 +1382,14 @@ def load_model(path: str, driver_version="tpu_driver0.1_dev20210607", hf_checkpo
else:
try:
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:
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:
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:
model = AutoModelForCausalLM.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache")
except Exception as e: