Restore Lowmem
Accidentally got replaced in one of my test runs
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parent
25a6e489c1
commit
cae0f279e2
12
aiserver.py
12
aiserver.py
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@ -876,25 +876,25 @@ if(not vars.model in ["InferKit", "Colab", "OAI", "ReadOnly", "TPUMeshTransforme
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with(maybe_use_float16()):
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with(maybe_use_float16()):
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tokenizer = GPT2TokenizerFast.from_pretrained(vars.custmodpth, cache_dir="cache/")
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tokenizer = GPT2TokenizerFast.from_pretrained(vars.custmodpth, cache_dir="cache/")
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try:
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try:
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model = AutoModelForCausalLM.from_pretrained(vars.custmodpth, cache_dir="cache/", **maybe_low_cpu_mem_usage())
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model = AutoModelForCausalLM.from_pretrained(vars.custmodpth, cache_dir="cache/", **lowmem)
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except ValueError as e:
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except ValueError as e:
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model = GPTNeoForCausalLM.from_pretrained(vars.custmodpth, cache_dir="cache/", **maybe_low_cpu_mem_usage())
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model = GPTNeoForCausalLM.from_pretrained(vars.custmodpth, cache_dir="cache/", **lowmem)
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elif(os.path.isdir(vars.model.replace('/', '_'))):
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elif(os.path.isdir(vars.model.replace('/', '_'))):
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with(maybe_use_float16()):
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with(maybe_use_float16()):
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tokenizer = GPT2TokenizerFast.from_pretrained(vars.model.replace('/', '_'), cache_dir="cache/")
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tokenizer = GPT2TokenizerFast.from_pretrained(vars.model.replace('/', '_'), cache_dir="cache/")
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try:
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try:
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model = AutoModelForCausalLM.from_pretrained(vars.model.replace('/', '_'), cache_dir="cache/", **maybe_low_cpu_mem_usage())
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model = AutoModelForCausalLM.from_pretrained(vars.model.replace('/', '_'), cache_dir="cache/", **lowmem)
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except ValueError as e:
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except ValueError as e:
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model = GPTNeoForCausalLM.from_pretrained(vars.model.replace('/', '_'), cache_dir="cache/", **maybe_low_cpu_mem_usage())
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model = GPTNeoForCausalLM.from_pretrained(vars.model.replace('/', '_'), cache_dir="cache/", **lowmem)
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else:
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else:
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print("Model does not exist locally, attempting to download from Huggingface...")
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print("Model does not exist locally, attempting to download from Huggingface...")
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tokenizer = GPT2TokenizerFast.from_pretrained(vars.model, cache_dir="cache/")
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tokenizer = GPT2TokenizerFast.from_pretrained(vars.model, cache_dir="cache/")
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with(maybe_use_float16()):
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with(maybe_use_float16()):
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tokenizer = GPT2TokenizerFast.from_pretrained(vars.model, cache_dir="cache/")
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tokenizer = GPT2TokenizerFast.from_pretrained(vars.model, cache_dir="cache/")
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try:
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try:
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model = AutoModelForCausalLM.from_pretrained(vars.model, cache_dir="cache/", **maybe_low_cpu_mem_usage())
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model = AutoModelForCausalLM.from_pretrained(vars.model, cache_dir="cache/", **lowmem)
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except ValueError as e:
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except ValueError as e:
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model = GPTNeoForCausalLM.from_pretrained(vars.model, cache_dir="cache/", **maybe_low_cpu_mem_usage())
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model = GPTNeoForCausalLM.from_pretrained(vars.model, cache_dir="cache/", **lowmem)
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model = model.half()
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model = model.half()
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import shutil
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import shutil
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shutil.rmtree("cache/")
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shutil.rmtree("cache/")
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