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Remove except Exception so that errors actually show up

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0cc4m
2023-03-16 05:19:47 +00:00
parent b3b454bbe4
commit 5d17692c79
1 changed files with 7 additions and 12 deletions
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19
aiserver.py
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@@ -3128,20 +3128,15 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal
# tokenizer = GPT2Tokenizer.from_pretrained(koboldai_vars.custmodpth, revision=koboldai_vars.revision, cache_dir="cache")
# except Exception as e:
# tokenizer = GPT2Tokenizer.from_pretrained("gpt2", revision=koboldai_vars.revision, cache_dir="cache")
try:
# model = AutoModelForCausalLM.from_pretrained(koboldai_vars.custmodpth, revision=koboldai_vars.revision, cache_dir="cache", **lowmem)
if os.environ.get('LLAMA_4BIT') is not None:
model = load_quant(koboldai_vars.custmodpth, os.environ['LLAMA_4BIT'], 4)
else:
raise RuntimeError("It looks like your environment variable for LLAMA_4BIT is not set (the model path).\nPlease set this variable before proceeding.")
# model = AutoModelForCausalLM.from_pretrained(koboldai_vars.custmodpth, revision=koboldai_vars.revision, cache_dir="cache", **lowmem)
if model is None:
raise RuntimeError("Model returned 'None'. This is not expected to happen, but due to this, the model will not load.")
if os.environ.get('LLAMA_4BIT'):
model = load_quant(koboldai_vars.custmodpth, os.environ['LLAMA_4BIT'], 4)
else:
raise RuntimeError("It looks like your environment variable for LLAMA_4BIT is not set (the model path).\nPlease set this variable before proceeding.")
except Exception as e:
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.")
# model = GPTNeoForCausalLM.from_pretrained(koboldai_vars.custmodpth, revision=koboldai_vars.revision, cache_dir="cache", **lowmem)
if model is None:
raise RuntimeError("Model returned 'None'. This is not expected to happen, but due to this, the model will not load.")
elif(os.path.isdir("models/{}".format(koboldai_vars.model.replace('/', '_')))):
try:
tokenizer = AutoTokenizer.from_pretrained("models/{}".format(koboldai_vars.model.replace('/', '_')), revision=koboldai_vars.revision, cache_dir="cache", use_fast=False)