Use ExLlamaV2 (instead of the HF one) for EXL2 models for now

It doesn't seem to have the "OverflowError" bug

modules/loaders.py

@@ -110,7 +110,6 @@ loaders_and_params = OrderedDict({
         'no_flash_attn',
         'no_xformers',
         'no_sdpa',
-        'exllamav2_info',
     ],
     'HQQ': [
         'hqq_backend',

modules/models_settings.py

@@ -172,11 +172,11 @@ def infer_loader(model_name, model_settings, hf_quant_method=None):
     elif hf_quant_method == 'exl3':
         loader = 'ExLlamav3_HF'
     elif hf_quant_method in ['exl2', 'gptq']:
-        loader = 'ExLlamav2_HF'
+        loader = 'ExLlamav2'
     elif re.match(r'.*exl3', model_name.lower()):
         loader = 'ExLlamav3_HF'
     elif re.match(r'.*exl2', model_name.lower()):
-        loader = 'ExLlamav2_HF'
+        loader = 'ExLlamav2'
     elif re.match(r'.*-hqq', model_name.lower()):
         return 'HQQ'
     else:

modules/ui_model_menu.py

@@ -133,7 +133,6 @@ def create_ui():
                             shared.gradio['trust_remote_code'] = gr.Checkbox(label="trust-remote-code", value=shared.args.trust_remote_code, info='Set trust_remote_code=True while loading the tokenizer/model. To enable this option, start the web UI with the --trust-remote-code flag.', interactive=shared.args.trust_remote_code)
                             shared.gradio['no_use_fast'] = gr.Checkbox(label="no_use_fast", value=shared.args.no_use_fast, info='Set use_fast=False while loading the tokenizer.')
                             shared.gradio['llamacpp_HF_info'] = gr.Markdown("llamacpp_HF loads llama.cpp as a Transformers model. To use it, you need to place your GGUF in a subfolder of models/ with the necessary tokenizer files.\n\nYou can use the \"llamacpp_HF creator\" menu to do that automatically.")
-                            shared.gradio['exllamav2_info'] = gr.Markdown("ExLlamav2_HF is recommended over ExLlamav2 for better integration with extensions and more consistent sampling behavior across loaders.")
                             shared.gradio['tensorrt_llm_info'] = gr.Markdown('* TensorRT-LLM has to be installed manually in a separate Python 3.10 environment at the moment. For a guide, consult the description of [this PR](https://github.com/oobabooga/text-generation-webui/pull/5715). \n\n* `max_seq_len` is only used when `cpp-runner` is checked.\n\n* `cpp_runner` does not support streaming at the moment.')
 
             with gr.Column():