Fix hidden size detection for GPTJForCausalLM
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@ -600,17 +600,20 @@ if(not vars.model in ["InferKit", "Colab", "OAI", "ReadOnly"]):
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try:
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try:
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return int(model.transformer.hidden_size)
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return int(model.transformer.hidden_size)
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except:
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except:
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try:
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return int(model.transformer.embed_dim)
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return int(model.transformer.embed_dim)
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except:
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return int(model.lm_head.in_features)
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# If custom GPT Neo model was chosen
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# If custom GPT Neo model was chosen
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if(vars.model == "NeoCustom"):
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if(vars.model == "NeoCustom"):
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model_config = open(vars.custmodpth + "/config.json", "r")
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model_config = open(vars.custmodpth + "/config.json", "r")
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js = json.load(model_config)
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js = json.load(model_config)
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vars.modeldim = int(js['hidden_size'])
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if("model_type" in js):
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if("model_type" in js):
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model = AutoModelForCausalLM.from_pretrained(vars.custmodpth)
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model = AutoModelForCausalLM.from_pretrained(vars.custmodpth)
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else:
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else:
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model = GPTNeoForCausalLM.from_pretrained(vars.custmodpth)
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model = GPTNeoForCausalLM.from_pretrained(vars.custmodpth)
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vars.modeldim = get_hidden_size_from_model(model)
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tokenizer = GPT2Tokenizer.from_pretrained(vars.custmodpth)
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tokenizer = GPT2Tokenizer.from_pretrained(vars.custmodpth)
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# Is CUDA available? If so, use GPU, otherwise fall back to CPU
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# Is CUDA available? If so, use GPU, otherwise fall back to CPU
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if(vars.hascuda):
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if(vars.hascuda):
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