Merge branch 'main' into nightly

unsloth/import_fixes.py

@@ -101,7 +101,9 @@ if os.environ.get("UNSLOTH_ENABLE_LOGGING", "0") != "1":
     # Skipping import of cpp extensions due to incompatible torch version 2.9.0+cu128 for torchao version 0.15.0
     logging.getLogger("torchao").setLevel(logging.ERROR)
     # SyntaxWarning: invalid escape sequence '\.'
-    warnings.filterwarnings("ignore", message = "invalid escape sequence", category = SyntaxWarning)
+    warnings.filterwarnings(
+        "ignore", message = "invalid escape sequence", category = SyntaxWarning
+    )
 
 
 # Fix up AttributeError: 'MessageFactory' object has no attribute 'GetPrototype'
@@ -549,5 +551,8 @@ def fix_diffusers_warnings():
 def fix_huggingface_hub():
     # huggingface_hub.is_offline_mode got removed, so add it back
     import huggingface_hub
+
     if not hasattr(huggingface_hub, "is_offline_mode"):
-        huggingface_hub.is_offline_mode = lambda: huggingface_hub.constants.HF_HUB_OFFLINE
+        huggingface_hub.is_offline_mode = (
+            lambda: huggingface_hub.constants.HF_HUB_OFFLINE
+        )

unsloth/models/_utils.py

@@ -73,6 +73,7 @@ __all__ = [
     "verify_fp8_support_if_applicable",
     "_get_inference_mode_context_manager",
     "hf_login",
+    "make_fast_generate_wrapper",
 ]
 
 import torch
@@ -2378,3 +2379,59 @@ def hf_login(token: Optional[str] = None) -> Optional[str]:
     except Exception as e:
         logger.info(f"Failed to login to huggingface using token with error: {e}")
     return token
+
+
+def make_fast_generate_wrapper(original_generate):
+    """
+    Creates a wrapper around model.generate that checks for incorrect
+    vLLM-style usage when fast_inference=False.
+    """
+
+    @functools.wraps(original_generate)
+    def _fast_generate_wrapper(*args, **kwargs):
+        # Check for vLLM-specific arguments
+        if "sampling_params" in kwargs:
+            raise ValueError(
+                "Unsloth: `sampling_params` is only supported when `fast_inference=True` (vLLM). "
+                "Since `fast_inference=False`, use HuggingFace generate arguments instead:\n"
+                "  model.fast_generate(**tokens.to('cuda'), max_new_tokens=64, temperature=1.0, top_p=0.95)"
+            )
+
+        if "lora_request" in kwargs:
+            raise ValueError(
+                "Unsloth: `lora_request` is only supported when `fast_inference=True` (vLLM). "
+                "Since `fast_inference=False`, LoRA weights are already merged into the model."
+            )
+
+        # Check if first positional argument is a string or list of strings
+        if len(args) > 0:
+            first_arg = args[0]
+            is_string_input = False
+
+            if isinstance(first_arg, str):
+                is_string_input = True
+            elif isinstance(first_arg, (list, tuple)) and len(first_arg) > 0:
+                if isinstance(first_arg[0], str):
+                    is_string_input = True
+
+            if is_string_input:
+                raise ValueError(
+                    "Unsloth: Passing text strings to `fast_generate` is only supported "
+                    "when `fast_inference=True` (vLLM). Since `fast_inference=False`, you must "
+                    "tokenize the input first:\n\n"
+                    "  messages = tokenizer.apply_chat_template(\n"
+                    '      [{"role": "user", "content": "Your prompt here"}],\n'
+                    "      tokenize=True, add_generation_prompt=True,\n"
+                    '      return_tensors="pt", return_dict=True\n'
+                    "  )\n"
+                    "  output = model.fast_generate(\n"
+                    "      **messages.to('cuda'),\n"
+                    "      max_new_tokens=64,\n"
+                    "      temperature=1.0,\n"
+                    "  )"
+                )
+
+        # Call original generate
+        return original_generate(*args, **kwargs)
+
+    return _fast_generate_wrapper

unsloth/models/llama.py

@@ -2326,7 +2326,7 @@ class FastLlamaModel:
                 attn_implementation = "eager",
                 **kwargs,
             )
-            model.fast_generate = model.generate
+            model.fast_generate = make_fast_generate_wrapper(model.generate)
             model.fast_generate_batches = None
         else:
             from unsloth_zoo.vllm_utils import (

unsloth/models/vision.py

@@ -673,7 +673,7 @@ class FastBaseModel:
                 **kwargs,
             )
             if hasattr(model, "generate"):
-                model.fast_generate = model.generate
+                model.fast_generate = make_fast_generate_wrapper(model.generate)
                 model.fast_generate_batches = error_out_no_vllm
             if offload_embedding:
                 if bool(