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@@ -18,7 +18,7 @@ model_name = 'galactica-6.7b'
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#model_name = 'flan-t5'
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#model_name = 'OPT-13B-Erebus'
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-settings_name = "Default"
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+loaded_preset = None
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def load_model(model_name):
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print(f"Loading {model_name}...")
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@@ -31,7 +31,7 @@ def load_model(model_name):
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model = AutoModelForCausalLM.from_pretrained(f"models/{model_name}", device_map='auto', load_in_8bit=True)
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elif model_name in ['gpt-j-6B']:
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model = AutoModelForCausalLM.from_pretrained(f"models/{model_name}", low_cpu_mem_usage=True, torch_dtype=torch.float16).cuda()
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- elif model_name in ['flan-t5']:
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+ elif model_name in ['flan-t5', 't5-large']:
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model = T5ForConditionalGeneration.from_pretrained(f"models/{model_name}").cuda()
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if model_name in ['gpt4chan_model_float16']:
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@@ -41,7 +41,7 @@ def load_model(model_name):
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else:
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tokenizer = AutoTokenizer.from_pretrained(f"models/{model_name}/")
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- print(f"Loaded the model in {time.time()-t0} seconds.")
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+ print(f"Loaded the model in {(time.time()-t0):.2f} seconds.")
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return model, tokenizer
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def fix_gpt4chan(s):
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@@ -53,7 +53,7 @@ def fix_gpt4chan(s):
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return s
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def fn(question, temperature, max_length, inference_settings, selected_model):
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- global model, tokenizer, model_name, settings_name
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+ global model, tokenizer, model_name, loaded_preset, preset
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if selected_model != model_name:
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model_name = selected_model
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@@ -61,10 +61,10 @@ def fn(question, temperature, max_length, inference_settings, selected_model):
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tokenier = None
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torch.cuda.empty_cache()
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model, tokenizer = load_model(model_name)
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- if inference_settings != settings_name:
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+ if inference_settings != loaded_preset:
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with open(f'presets/{inference_settings}.txt', 'r') as infile:
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preset = infile.read()
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- settings_name = inference_settings
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+ loaded_preset = inference_settings
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torch.cuda.empty_cache()
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input_text = question
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@@ -92,7 +92,7 @@ interface = gr.Interface(
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gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Temperature', value=0.7),
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gr.Slider(minimum=1, maximum=2000, step=1, label='max_length', value=200),
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gr.Dropdown(choices=list(map(lambda x : x.split('/')[-1].split('.')[0], glob.glob("presets/*.txt"))), value="Default"),
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- gr.Dropdown(choices=["gpt4chan_model_float16", "galactica-6.7b", "opt-6.7b", "opt-13b", "gpt-neox-20b", "gpt-j-6B-float16", "flan-t5", "bloomz-7b1-p3", "OPT-13B-Erebus"], value=model_name),
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+ gr.Dropdown(choices=sorted(set(map(lambda x : x.split('/')[-1].replace('.pt', ''), glob.glob("models/*") + glob.glob("torch-dumps/*")))), value=model_name),
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],
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outputs=[
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gr.Textbox(placeholder="", lines=15),
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oobabooga