Add AutoAWQ integration

outlines/models/awq.py

@@ -0,0 +1,45 @@
+from typing import TYPE_CHECKING, Optional
+
+from .transformers import Transformer, TransformerTokenizer
+
+if TYPE_CHECKING:
+    from transformers import PreTrainedModel, PreTrainedTokenizer
+
+
+class AWQModel(Transformer):
+    """Represents a `transformers` model."""
+
+    def __init__(
+        self,
+        model: "PreTrainedModel",
+        tokenizer: "PreTrainedTokenizer",
+    ):
+        self.device = model.model.device
+        self.model = model
+        self.tokenizer = tokenizer
+
+
+def awq(
+    model_name: str,
+    fuse_layers: bool = True,
+    device: Optional[str] = None,
+    model_kwargs: dict = {},
+    tokenizer_kwargs: dict = {},
+):
+    try:
+        from awq import AutoAWQForCausalLM
+    except ImportError:
+        raise ImportError(
+            "The `autoawq` and `transformers` library needs to be installed in order to use `AutoAWQ` models."
+        )
+
+    model_kwargs["fuse_layers"] = fuse_layers
+    model_kwargs["safetensors"] = True
+
+    if device is not None:
+        model_kwargs["device_map"] = device
+
+    model = AutoAWQForCausalLM.from_quantized(model_name, **model_kwargs)
+    tokenizer = TransformerTokenizer(model_name, trust_remote_code=True)
+
+    return AWQModel(model, tokenizer)

pyproject.toml

@@ -87,6 +87,8 @@ exclude=["examples"]
 
 [[tool.mypy.overrides]]
 module = [
+    "awq.*",
+    "auto_gptq.*",
     "jinja2",
     "joblib.*",
     "jsonschema.*",