Expose config through the cli arguments

transformers/commands/run.py

@@ -16,7 +16,7 @@ def try_infer_format_from_ext(path: str):
 
 
 def run_command_factory(args):
-    nlp = pipeline(task=args.task, model=args.model, tokenizer=args.tokenizer, device=args.device)
+    nlp = pipeline(task=args.task, model=args.model, config=args.config, tokenizer=args.tokenizer, device=args.device)
     format = try_infer_format_from_ext(args.input) if args.format == 'infer' else args.format
     reader = PipelineDataFormat.from_str(format, args.output, args.input, args.column)
     return RunCommand(nlp, reader)
@@ -34,6 +34,7 @@ class RunCommand(BaseTransformersCLICommand):
         run_parser.add_argument('--device', type=int, default=-1, help='Indicate the device to run onto, -1 indicates CPU, >= 0 indicates GPU (default: -1)')
         run_parser.add_argument('--task', choices=SUPPORTED_TASKS.keys(), help='Task to run')
         run_parser.add_argument('--model', type=str, required=True, help='Name or path to the model to instantiate.')
+        run_parser.add_argument('--config', type=str, help='Name or path to the model\'s config to instantiate.')
         run_parser.add_argument('--tokenizer', type=str, help='Name of the tokenizer to use. (default: same as the model name)')
         run_parser.add_argument('--column', type=str, required=True, help='Name of the column to use as input. (For multi columns input as QA use column1,columns2)')
         run_parser.add_argument('--format', type=str, default='infer', choices=PipelineDataFormat.SUPPORTED_FORMATS, help='Input format to read from')