Backend cleanup (#6025)

modules/models.py

@@ -73,13 +73,11 @@ def load_model(model_name, loader=None):
     load_func_map = {
         'Transformers': huggingface_loader,
         'AutoGPTQ': AutoGPTQ_loader,
-        'GPTQ-for-LLaMa': GPTQ_loader,
         'llama.cpp': llamacpp_loader,
         'llamacpp_HF': llamacpp_HF_loader,
         'ExLlamav2': ExLlamav2_loader,
         'ExLlamav2_HF': ExLlamav2_HF_loader,
         'AutoAWQ': AutoAWQ_loader,
-        'QuIP#': QuipSharp_loader,
         'HQQ': HQQ_loader,
     }
 
@@ -310,55 +308,6 @@ def AutoAWQ_loader(model_name):
     return model
 
 
-def QuipSharp_loader(model_name):
-    try:
-        with RelativeImport("repositories/quip-sharp"):
-            from lib.utils.unsafe_import import model_from_hf_path
-    except:
-        logger.error(
-            "\nQuIP# has not been found. It must be installed manually for now.\n"
-            "For instructions on how to do that, please consult:\n"
-            "https://github.com/oobabooga/text-generation-webui/pull/4803\n"
-        )
-        return None, None
-
-    # This fixes duplicate logging messages after the import above.
-    handlers = logging.getLogger().handlers
-    if len(handlers) > 1:
-        logging.getLogger().removeHandler(handlers[1])
-
-    model_dir = Path(f'{shared.args.model_dir}/{model_name}')
-    if not all((model_dir / file).exists() for file in ['tokenizer_config.json', 'special_tokens_map.json', 'tokenizer.model']):
-        logger.error(f"Could not load the model because the tokenizer files could not be found in the model folder. Please download the following files from the original (unquantized) model into {model_dir}: special_tokens_map.json, tokenizer.json, tokenizer.model, tokenizer_config.json.")
-        return None, None
-
-    model, model_str = model_from_hf_path(
-        model_dir,
-        use_cuda_graph=False,
-        use_flash_attn=not shared.args.no_flash_attn
-    )
-
-    return model
-
-
-def GPTQ_loader(model_name):
-
-    # Monkey patch
-    if shared.args.monkey_patch:
-        logger.warning("Applying the monkey patch for using LoRAs with GPTQ models. It may cause undefined behavior outside its intended scope.")
-        from modules.monkey_patch_gptq_lora import load_model_llama
-
-        model, _ = load_model_llama(model_name)
-
-    # No monkey patch
-    else:
-        import modules.GPTQ_loader
-
-        model = modules.GPTQ_loader.load_quantized(model_name)
-
-    return model
-
-
 def AutoGPTQ_loader(model_name):
     import modules.AutoGPTQ_loader
 
@@ -380,12 +329,12 @@ def ExLlamav2_HF_loader(model_name):
 
 def HQQ_loader(model_name):
     from hqq.core.quantize import HQQBackend, HQQLinear
-    from hqq.engine.hf import HQQModelForCausalLM
+    from hqq.models.hf.base import AutoHQQHFModel
 
     logger.info(f"Loading HQQ model with backend: \"{shared.args.hqq_backend}\"")
 
     model_dir = Path(f'{shared.args.model_dir}/{model_name}')
-    model = HQQModelForCausalLM.from_quantized(str(model_dir))
+    model = AutoHQQHFModel.from_quantized(str(model_dir))
     HQQLinear.set_backend(getattr(HQQBackend, shared.args.hqq_backend))
     return model