diff --git a/aiserver.py b/aiserver.py index 406eb01d..d9ed0088 100644 --- a/aiserver.py +++ b/aiserver.py @@ -1034,7 +1034,7 @@ def getmodelname(): if(koboldai_vars.online_model != ''): return(f"{koboldai_vars.model}/{koboldai_vars.online_model}") if(koboldai_vars.model in ("NeoCustom", "GPT2Custom", "TPUMeshTransformerGPTJ", "TPUMeshTransformerGPTNeoX")): - modelname = os.path.basename(os.path.normpath(koboldai_vars.custmodpth)) + modelname = os.path.basename(os.path.normpath(model.path)) return modelname else: modelname = koboldai_vars.model if koboldai_vars.model is not None else "Read Only" @@ -1687,6 +1687,9 @@ def load_model(model_backend, initial_load=False): model = model_backends[model_backend] model.load(initial_load=initial_load, save_model=not (args.colab or args.cacheonly) or args.savemodel) koboldai_vars.model = model.model_name if "model_name" in vars(model) else model.id #Should have model_name, but it could be set to id depending on how it's setup + if koboldai_vars.model in ("NeoCustom", "GPT2Custom", "TPUMeshTransformerGPTJ", "TPUMeshTransformerGPTNeoX"): + koboldai_vars.model = os.path.basename(os.path.normpath(model.path)) + logger.info(koboldai_vars.model) logger.debug("Model Type: {}".format(koboldai_vars.model_type)) # TODO: Convert everywhere to use model.tokenizer diff --git a/modeling/inference_models/generic_hf_torch/class.py b/modeling/inference_models/generic_hf_torch/class.py index bbd42096..fd4c2a1a 100644 --- a/modeling/inference_models/generic_hf_torch/class.py +++ b/modeling/inference_models/generic_hf_torch/class.py @@ -41,7 +41,7 @@ class model_backend(HFTorchInferenceModel): if self.model_name == "NeoCustom": self.model_name = os.path.basename( - os.path.normpath(utils.koboldai_vars.custmodpth) + os.path.normpath(self.path) ) utils.koboldai_vars.model = self.model_name diff --git a/modeling/inference_models/hf.py b/modeling/inference_models/hf.py index c7bfdee4..5987a1ce 100644 --- a/modeling/inference_models/hf.py +++ b/modeling/inference_models/hf.py @@ -188,6 +188,7 @@ class HFInferenceModel(InferenceModel): self.usegpu = parameters['use_gpu'] if 'use_gpu' in parameters else None self.breakmodel = False self.lazy_load = False + logger.info(parameters) self.model_name = parameters['custom_model_name'] if 'custom_model_name' in parameters else parameters['id'] self.path = parameters['path'] if 'path' in parameters else None