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KoboldAI-Client
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Fix some more typos in prompt_tuner.py

This commit is contained in:
vfbd 2022-08-22 16:51:09 -04:00
parent a49a633164
commit f79926b73d
1 changed files with 12 additions and 12 deletions
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24
prompt_tuner.py
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@ -127,28 +127,28 @@ def get_tokenizer(model_id, revision=None) -> transformers.PreTrainedTokenizerBa
tokenizer = GPT2TokenizerFast.from_pretrained(model_id, revision=revision, cache_dir="cache") tokenizer = GPT2TokenizerFast.from_pretrained(model_id, revision=revision, cache_dir="cache")
except Exception as e: except Exception as e:
tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=revision, cache_dir="cache") tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=revision, cache_dir="cache")
elif(os.path.isdir("models/{}".format(vars.model.replace('/', '_')))): elif(os.path.isdir("models/{}".format(model_id.replace('/', '_')))):
try: try:
tokenizer = AutoTokenizer.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=revision, cache_dir="cache") tokenizer = AutoTokenizer.from_pretrained("models/{}".format(model_id.replace('/', '_')), revision=revision, cache_dir="cache")
except Exception as e: except Exception as e:
pass pass
try: try:
tokenizer = AutoTokenizer.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=revision, cache_dir="cache", use_fast=False) tokenizer = AutoTokenizer.from_pretrained("models/{}".format(model_id.replace('/', '_')), revision=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=revision, cache_dir="cache") tokenizer = GPT2TokenizerFast.from_pretrained("models/{}".format(model_id.replace('/', '_')), revision=revision, cache_dir="cache")
except Exception as e: except Exception as e:
tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=revision, cache_dir="cache") tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=revision, cache_dir="cache")
else: else:
try: try:
tokenizer = AutoTokenizer.from_pretrained(vars.model, revision=revision, cache_dir="cache") tokenizer = AutoTokenizer.from_pretrained(model_id, revision=revision, cache_dir="cache")
except Exception as e: except Exception as e:
pass pass
try: try:
tokenizer = AutoTokenizer.from_pretrained(vars.model, revision=revision, cache_dir="cache", use_fast=False) tokenizer = AutoTokenizer.from_pretrained(model_id, revision=revision, cache_dir="cache", use_fast=False)
except Exception as e: except Exception as e:
try: try:
tokenizer = GPT2TokenizerFast.from_pretrained(vars.model, revision=revision, cache_dir="cache") tokenizer = GPT2TokenizerFast.from_pretrained(model_id, revision=revision, cache_dir="cache")
except Exception as e: except Exception as e:
tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=revision, cache_dir="cache") tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=revision, cache_dir="cache")
@ -474,20 +474,20 @@ class TrainerBase(abc.ABC):
if("out of memory" in traceback.format_exc().lower()): if("out of memory" in traceback.format_exc().lower()):
raise RuntimeError("One of your GPUs ran out of memory when KoboldAI tried to load your model.") raise RuntimeError("One of your GPUs ran out of memory when KoboldAI tried to load your model.")
model = GPTNeoPromptTuningLM.from_pretrained(self.data.ckpt_path, revision=REVISION, cache_dir="cache") model = GPTNeoPromptTuningLM.from_pretrained(self.data.ckpt_path, revision=REVISION, cache_dir="cache")
elif(os.path.isdir("models/{}".format(vars.model.replace('/', '_')))): elif(os.path.isdir("models/{}".format(self.data.ckpt_path.replace('/', '_')))):
try: try:
model = AutoPromptTuningLM.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=REVISION, cache_dir="cache") model = AutoPromptTuningLM.from_pretrained("models/{}".format(self.data.ckpt_path.replace('/', '_')), revision=REVISION, cache_dir="cache")
except Exception as e: except Exception as e:
if("out of memory" in traceback.format_exc().lower()): if("out of memory" in traceback.format_exc().lower()):
raise RuntimeError("One of your GPUs ran out of memory when KoboldAI tried to load your model.") raise RuntimeError("One of your GPUs ran out of memory when KoboldAI tried to load your model.")
model = GPTNeoPromptTuningLM.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=REVISION, cache_dir="cache") model = GPTNeoPromptTuningLM.from_pretrained("models/{}".format(self.data.ckpt_path.replace('/', '_')), revision=REVISION, cache_dir="cache")
else: else:
try: try:
model = AutoPromptTuningLM.from_pretrained(vars.model, revision=REVISION, cache_dir="cache") model = AutoPromptTuningLM.from_pretrained(self.data.ckpt_path, revision=REVISION, cache_dir="cache")
except Exception as e: except Exception as e:
if("out of memory" in traceback.format_exc().lower()): if("out of memory" in traceback.format_exc().lower()):
raise RuntimeError("One of your GPUs ran out of memory when KoboldAI tried to load your model.") raise RuntimeError("One of your GPUs ran out of memory when KoboldAI tried to load your model.")
model = GPTNeoPromptTuningLM.from_pretrained(vars.model, revision=REVISION, cache_dir="cache") model = GPTNeoPromptTuningLM.from_pretrained(self.data.ckpt_path, revision=REVISION, cache_dir="cache")
if step == 0: if step == 0:
soft_embeddings = self.get_initial_soft_embeddings(model) soft_embeddings = self.get_initial_soft_embeddings(model)