Update Lua modeltype and model API
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c305076cf3
commit
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23
aiserver.py
23
aiserver.py
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@ -82,6 +82,7 @@ class vars:
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submission = "" # Same as above, but after applying input formatting
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lastctx = "" # The last context submitted to the generator
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model = "" # Model ID string chosen at startup
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model_orig = "" # Original model string before being changed by auto model type detection
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model_type = "" # Model Type (Automatically taken from the model config)
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noai = False # Runs the script without starting up the transformers pipeline
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aibusy = False # Stops submissions while the AI is working
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@ -184,7 +185,7 @@ def getModelSelection():
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while(vars.model == ''):
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modelsel = input("Model #> ")
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if(modelsel.isnumeric() and int(modelsel) > 0 and int(modelsel) <= len(modellist)):
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vars.model = modellist[int(modelsel)-1][1]
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vars.model = vars.model_orig = modellist[int(modelsel)-1][1]
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else:
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print("{0}Please enter a valid selection.{1}".format(colors.RED, colors.END))
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@ -365,7 +366,7 @@ parser.add_argument("--override_rename", action='store_true', help="Renaming sto
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parser.add_argument("--configname", help="Force a fixed configuration name to aid with config management.")
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args = parser.parse_args()
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vars.model = args.model;
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vars.model = vars.model_orig = args.model;
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if args.remote:
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vars.remote = True;
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@ -1386,23 +1387,23 @@ def lua_get_modeltype():
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return "readonly"
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if(vars.model in ("Colab", "OAI", "InferKit")):
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return "api"
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if(vars.model in ("GPT2Custom", "NeoCustom")):
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if(vars.model not in ("TPUMeshTransformerGPTJ",) and (vars.model in ("GPT2Custom", "NeoCustom") or vars.model_type in ("gpt2", "gpt_neo", "gptj"))):
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hidden_size = get_hidden_size_from_model(model)
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if(vars.model in ("gpt2",) or (vars.model == "GPT2Custom" and hidden_size == 768)):
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if(vars.model in ("gpt2",) or (vars.model_type == "gpt2" and hidden_size == 768)):
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return "gpt2"
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if(vars.model in ("gpt2-medium",) or (vars.model == "GPT2Custom" and hidden_size == 1024)):
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if(vars.model in ("gpt2-medium",) or (vars.model_type == "gpt2" and hidden_size == 1024)):
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return "gpt2-medium"
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if(vars.model in ("gpt2-large",) or (vars.model == "GPT2Custom" and hidden_size == 1280)):
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if(vars.model in ("gpt2-large",) or (vars.model_type == "gpt2" and hidden_size == 1280)):
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return "gpt2-large"
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if(vars.model in ("gpt2-xl",) or (vars.model == "GPT2Custom" and hidden_size == 1600)):
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if(vars.model in ("gpt2-xl",) or (vars.model_type == "gpt2" and hidden_size == 1600)):
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return "gpt2-xl"
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if(vars.model == "NeoCustom" and hidden_size == 768):
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if(vars.model_type == "gpt_neo" and hidden_size == 768):
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return "gpt-neo-125M"
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if(vars.model in ("EleutherAI/gpt-neo-1.3B",) or (vars.model == "NeoCustom" and hidden_size == 2048)):
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if(vars.model in ("EleutherAI/gpt-neo-1.3B",) or (vars.model_type == "gpt_neo" and hidden_size == 2048)):
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return "gpt-neo-1.3B"
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if(vars.model in ("EleutherAI/gpt-neo-2.7B",) or (vars.model == "NeoCustom" and hidden_size == 2560)):
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if(vars.model in ("EleutherAI/gpt-neo-2.7B",) or (vars.model_type == "gpt_neo" and hidden_size == 2560)):
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return "gpt-neo-2.7B"
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if(vars.model in ("EleutherAI/gpt-j-6B",) or (vars.model == "NeoCustom" and hidden_size == 4096) or (vars.model == "TPUMeshTransformerGPTJ" and tpu_mtj_backend.params["d_model"] == 4096)):
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if(vars.model in ("EleutherAI/gpt-j-6B",) or (vars.model == "TPUMeshTransformerGPTJ" and tpu_mtj_backend.params["d_model"] == 4096) or (vars.model_type in ("gpt_neo", "gptj") and hidden_size == 4096)):
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return "gpt-j-6B"
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return "unknown"
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@ -1038,7 +1038,7 @@ return function(_python, _bridged)
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---@param t KoboldLib
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---@return string
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function KoboldLib_getters.model(t)
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return bridged.vars.model
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return bridged.vars.model_orig
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end
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---@param t KoboldLib
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