mirror of
https://github.com/KoboldAI/KoboldAI-Client.git
synced 2025-02-02 18:46:48 +01:00
Merge branch 'main' into merge
This commit is contained in:
commit
79ae0f17ec
33
aiserver.py
33
aiserver.py
@ -2491,15 +2491,14 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal
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if(os.path.isdir(vars.custmodpth)):
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if(os.path.isdir(vars.custmodpth)):
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try:
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try:
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tokenizer = AutoTokenizer.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache")
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tokenizer = AutoTokenizer.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache")
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except Exception as e:
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pass
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try:
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tokenizer = AutoTokenizer.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache", use_fast=False)
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except Exception as e:
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except Exception as e:
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try:
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try:
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tokenizer = GPT2TokenizerFast.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache")
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tokenizer = AutoTokenizer.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache", use_fast=False)
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except Exception as e:
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except Exception as e:
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tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
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try:
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tokenizer = GPT2TokenizerFast.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache")
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except Exception as e:
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tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
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try:
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try:
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model = AutoModelForCausalLM.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache", **lowmem)
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model = AutoModelForCausalLM.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache", **lowmem)
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except Exception as e:
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except Exception as e:
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@ -2509,15 +2508,14 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal
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elif(os.path.isdir("models/{}".format(vars.model.replace('/', '_')))):
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elif(os.path.isdir("models/{}".format(vars.model.replace('/', '_')))):
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try:
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try:
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tokenizer = AutoTokenizer.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache")
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tokenizer = AutoTokenizer.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache")
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except Exception as e:
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pass
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try:
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tokenizer = AutoTokenizer.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache", use_fast=False)
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except Exception as e:
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except Exception as e:
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try:
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try:
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tokenizer = GPT2TokenizerFast.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache")
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tokenizer = AutoTokenizer.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache", use_fast=False)
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except Exception as e:
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except Exception as e:
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tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
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try:
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tokenizer = GPT2TokenizerFast.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache")
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except Exception as e:
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tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
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try:
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try:
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model = AutoModelForCausalLM.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache", **lowmem)
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model = AutoModelForCausalLM.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache", **lowmem)
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except Exception as e:
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except Exception as e:
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@ -2540,15 +2538,14 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal
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try:
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try:
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tokenizer = AutoTokenizer.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache")
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tokenizer = AutoTokenizer.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache")
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except Exception as e:
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pass
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try:
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tokenizer = AutoTokenizer.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache", use_fast=False)
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except Exception as e:
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except Exception as e:
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try:
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try:
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tokenizer = GPT2TokenizerFast.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache")
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tokenizer = AutoTokenizer.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache", use_fast=False)
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except Exception as e:
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except Exception as e:
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tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
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try:
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tokenizer = GPT2TokenizerFast.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache")
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except Exception as e:
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tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
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try:
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try:
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model = AutoModelForCausalLM.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache", **lowmem)
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model = AutoModelForCausalLM.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache", **lowmem)
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except Exception as e:
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except Exception as e:
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@ -1646,26 +1646,29 @@ function chunkOnBeforeInput(event) {
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if(buildChunkSetFromNodeArray(getSelectedNodes()).size === 0) {
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if(buildChunkSetFromNodeArray(getSelectedNodes()).size === 0) {
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var s = rangy.getSelection();
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var s = rangy.getSelection();
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var r = s.getRangeAt(0);
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var r = s.getRangeAt(0);
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var rand = Math.random();
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if(document.queryCommandSupported && document.execCommand && document.queryCommandSupported('insertHTML')) {
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if(document.queryCommandSupported && document.execCommand && document.queryCommandSupported('insertHTML')) {
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document.execCommand('insertHTML', false, '<span id="_EDITOR_SENTINEL_">|</span>');
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document.execCommand('insertHTML', false, '<span id="_EDITOR_SENTINEL_' + rand + '_">|</span>');
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} else {
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} else {
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var t = document.createTextNode('|');
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var t = document.createTextNode('|');
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var b = document.createElement('span');
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var b = document.createElement('span');
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b.id = "_EDITOR_SENTINEL_";
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b.id = "_EDITOR_SENTINEL_" + rand + "_";
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b.insertNode(t);
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b.insertNode(t);
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r.insertNode(b);
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r.insertNode(b);
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}
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}
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var sentinel = document.getElementById("_EDITOR_SENTINEL_");
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setTimeout(function() {
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if(sentinel.nextSibling && sentinel.nextSibling.tagName === "CHUNK") {
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var sentinel = document.getElementById("_EDITOR_SENTINEL_" + rand + "_");
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r.selectNodeContents(sentinel.nextSibling);
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if(sentinel.nextSibling && sentinel.nextSibling.tagName === "CHUNK") {
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r.collapse(true);
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r.selectNodeContents(sentinel.nextSibling);
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} else if(sentinel.previousSibling && sentinel.previousSibling.tagName === "CHUNK") {
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r.collapse(true);
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r.selectNodeContents(sentinel.previousSibling);
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} else if(sentinel.previousSibling && sentinel.previousSibling.tagName === "CHUNK") {
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r.collapse(false);
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r.selectNodeContents(sentinel.previousSibling);
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}
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r.collapse(false);
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s.removeAllRanges();
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}
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s.addRange(r);
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s.removeAllRanges();
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sentinel.parentNode.removeChild(sentinel);
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s.addRange(r);
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sentinel.parentNode.removeChild(sentinel);
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}, 1);
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}
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}
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}
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}
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@ -18,7 +18,7 @@
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<script src="static/bootstrap.min.js"></script>
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<script src="static/bootstrap.min.js"></script>
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<script src="static/bootstrap-toggle.min.js"></script>
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<script src="static/bootstrap-toggle.min.js"></script>
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<script src="static/rangy-core.min.js"></script>
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<script src="static/rangy-core.min.js"></script>
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<script src="static/application.js?ver=1.18.1e"></script>
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<script src="static/application.js?ver=1.18.1f"></script>
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<script src="static/favicon.js"></script>
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<script src="static/favicon.js"></script>
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</head>
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</head>
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<body>
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<body>
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@ -1352,15 +1352,14 @@ def load_model(path: str, driver_version="tpu_driver0.1_dev20210607", hf_checkpo
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if(os.path.isdir(vars.custmodpth)):
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if(os.path.isdir(vars.custmodpth)):
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try:
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try:
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tokenizer = AutoTokenizer.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache")
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tokenizer = AutoTokenizer.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache")
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except Exception as e:
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pass
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try:
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tokenizer = AutoTokenizer.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache", use_fast=False)
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except Exception as e:
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except Exception as e:
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try:
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try:
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tokenizer = GPT2TokenizerFast.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache")
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tokenizer = AutoTokenizer.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache", use_fast=False)
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except Exception as e:
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except Exception as e:
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tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
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try:
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tokenizer = GPT2TokenizerFast.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache")
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except Exception as e:
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tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
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try:
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try:
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model = AutoModelForCausalLM.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache")
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model = AutoModelForCausalLM.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache")
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except Exception as e:
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except Exception as e:
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@ -1368,15 +1367,14 @@ def load_model(path: str, driver_version="tpu_driver0.1_dev20210607", hf_checkpo
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elif(os.path.isdir("models/{}".format(vars.model.replace('/', '_')))):
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elif(os.path.isdir("models/{}".format(vars.model.replace('/', '_')))):
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try:
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try:
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tokenizer = AutoTokenizer.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache")
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tokenizer = AutoTokenizer.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache")
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except Exception as e:
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pass
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try:
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tokenizer = AutoTokenizer.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache", use_fast=False)
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except Exception as e:
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except Exception as e:
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try:
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try:
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tokenizer = GPT2TokenizerFast.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache")
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tokenizer = AutoTokenizer.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache", use_fast=False)
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except Exception as e:
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except Exception as e:
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tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
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try:
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tokenizer = GPT2TokenizerFast.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache")
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except Exception as e:
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tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
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try:
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try:
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model = AutoModelForCausalLM.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache")
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model = AutoModelForCausalLM.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache")
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except Exception as e:
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except Exception as e:
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@ -1384,15 +1382,14 @@ def load_model(path: str, driver_version="tpu_driver0.1_dev20210607", hf_checkpo
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else:
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else:
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try:
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try:
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tokenizer = AutoTokenizer.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache")
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tokenizer = AutoTokenizer.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache")
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except Exception as e:
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pass
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try:
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tokenizer = AutoTokenizer.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache", use_fast=False)
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except Exception as e:
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except Exception as e:
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try:
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try:
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tokenizer = GPT2TokenizerFast.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache")
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tokenizer = AutoTokenizer.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache", use_fast=False)
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except Exception as e:
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except Exception as e:
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tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
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try:
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tokenizer = GPT2TokenizerFast.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache")
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except Exception as e:
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tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
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try:
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try:
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model = AutoModelForCausalLM.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache")
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model = AutoModelForCausalLM.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache")
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except Exception as e:
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except Exception as e:
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