TTS

pyproject.toml

@@ -37,7 +37,7 @@ triton = [
 ]
 
 huggingface = [
-    "unsloth_zoo>=2025.5.5",
+    "unsloth_zoo>=2025.5.6",
     "packaging",
     "tyro",
     "transformers==4.51.3,!=4.47.0",
@@ -381,7 +381,7 @@ colab-ampere-torch220 = [
     "flash-attn>=2.6.3",
 ]
 colab-new = [
-    "unsloth_zoo>=2025.5.5",
+    "unsloth_zoo>=2025.5.6",
     "packaging",
     "tyro",
     "transformers==4.51.3,!=4.47.0",

unsloth/chat_templates.py

@@ -1036,9 +1036,21 @@
     {%- endif %}
 {%- endif %}
 {%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
-{%- for message in messages[::-1] %}
+{%- for forward_message in messages %}
     {%- set index = (messages|length - 1) - loop.index0 %}
-    {%- if ns.multi_step_tool and message.role == "user" and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
+    {%- set message = messages[index] %}
+    {%- set current_content = message.content if message.content is not none else '' %}
+    {%- set tool_start = '<tool_response>' %}
+    {%- set tool_start_length = tool_start|length %}
+    {%- set start_of_message = current_content[:tool_start_length] %}
+    {%- set tool_end = '</tool_response>' %}
+    {%- set tool_end_length = tool_end|length %}
+    {%- set start_pos = (current_content|length) - tool_end_length %}
+    {%- if start_pos < 0 %}
+        {%- set start_pos = 0 %}
+    {%- endif %}
+    {%- set end_of_message = current_content[start_pos:] %}
+    {%- if ns.multi_step_tool and message.role == "user" and not(start_of_message == tool_start and end_of_message == tool_end) %}
         {%- set ns.multi_step_tool = false %}
         {%- set ns.last_query_index = index %}
     {%- endif %}
@@ -1053,8 +1065,9 @@
             {%- set reasoning_content = message.reasoning_content %}
         {%- else %}
             {%- if '</think>' in message.content %}
-                {%- set content = message.content.split('</think>')[-1].lstrip('\n') %}
-                {%- set reasoning_content = message.content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
+                {%- set content = (message.content.split('</think>')|last).lstrip('\n') %}
+                {%- set reasoning_content = (message.content.split('</think>')|first).rstrip('\n') %}
+                {%- set reasoning_content = (reasoning_content.split('<think>')|last).lstrip('\n') %}
             {%- endif %}
         {%- endif %}
         {%- if loop.index0 > ns.last_query_index %}
@@ -1110,7 +1123,7 @@
 qwen3_ollama = \
 '''
 FROM {__FILE_LOCATION__}
-TEMPLATE """{{ if .Messages }}
+TEMPLATE """{{- if .Messages }}
 {{- if or .System .Tools }}<|im_start|>system
 {{- if .System }}
 {{ .System }}
@@ -1161,8 +1174,12 @@
 {{ end }}<|im_start|>assistant
 {{ end }}{{ .Response }}{{ if .Response }}<|im_end|>{{ end }}"""
 PARAMETER stop "<|im_end|>"
-PARAMETER temperature 1.5
-PARAMETER min_p 0.1
+PARAMETER stop "<|im_start|>"
+PARAMETER temperature 0.6
+PARAMETER min_p 0.0
+PARAMETER top_k 20
+PARAMETER top_p 0.95
+PARAMETER repeat_penalty 1
 '''
 
 qwen3_template_eos_token = "<|im_end|>"

unsloth/models/_utils.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-__version__ = "2025.5.3"
+__version__ = "2025.5.4"
 
 __all__ = [
     "SUPPORTS_BFLOAT16",

unsloth/models/loader.py

@@ -541,10 +541,12 @@ def from_pretrained(
             if transformers_version < Version("4.50.0.dev0"):
                 raise RuntimeError("Unsloth: Granite Vision only works on transformers >= 4.50.0." + NIGHTLY)
         elif "csm-1b" in model_name.lower():
-            os.environ["UNSLOTH_COMPILE_DISABLE"] = "1"
-            os.environ["UNSLOTH_DISABLE_FAST_GENERATION"] = "1"
+            os.environ["UNSLOTH_DISABLE_STATIC_GENERATION"] = "1" # Sesame fails
+            os.environ["UNSLOTH_FORCE_CUSTOM_DTYPE"] = "torch.float16;if name.endswith(('_proj', 'fc1', 'fc2', 'codebook', 'head')): module.to(torch.float16)"
         elif "olmo-2" in model_name.lower() and transformers_version < Version("4.50.0.dev0"):
             raise RuntimeError("Unsloth: OLMo-2 only works on transformers >= 4.50.0." + NIGHTLY)
+        elif "whisper" in model_name.lower():
+            os.environ["UNSLOTH_DISABLE_STATIC_GENERATION"] = "1" # Whisper fails
         pass
 
         if USE_MODELSCOPE and not os.path.exists(model_name):

unsloth/models/mapper.py

@@ -817,6 +817,26 @@
         "microsoft/Phi-4-mini-reasoning",
         "unsloth/phi-4-mini-reasoning-bnb-4bit",
     ),
+    "unsloth/csm-1b" : (
+        "unsloth/csm-1b",
+        "sesame/csm-1b",
+    ),
+    "unsloth/whisper-large-v3" : (
+        "unsloth/whisper-large-v3",
+        "openai/whisper-large-v3",
+    ),
+    "unsloth/whisper-large-v3-turbo" : (
+        "unsloth/whisper-large-v3-turbo",
+        "openai/whisper-large-v3-turbo",
+    ),
+    "unsloth/whisper-small" : (
+        "unsloth/whisper-small",
+        "openai/whisper-small",
+    ),
+    "unsloth/CrisperWhisper" : (
+        "unsloth/CrisperWhisper",
+        "nyrahealth/CrisperWhisper",
+    ),
 }
 
 INT_TO_FLOAT_MAPPER  = {}

unsloth/models/vision.py

@@ -188,7 +188,10 @@ def unsloth_base_fast_generate(
     # Use hybrid if sliding window seen, otherwise try static
     cache_implementation = getattr(self.config, "cache_implementation", None)
     if getattr(self, "_supports_static_cache", True):
-        cache_implementation = "static"
+        if os.environ.get("UNSLOTH_DISABLE_STATIC_GENERATION", "0") == "0":
+            cache_implementation = "static"
+        else:
+            cache_implementation = None
     else:
         cache_implementation = None
     if cache_implementation is not None:
@@ -199,10 +202,10 @@ def unsloth_base_fast_generate(
             cache_implementation = "hybrid"
     if "generation_config" in kwargs:
         kwargs["generation_config"].cache_implementation = cache_implementation
-        kwargs["generation_config"].compile_config = _compile_config
+        kwargs["generation_config"].compile_config = _compile_config if cache_implementation is not None else None
     else:
         kwargs["cache_implementation"] = cache_implementation
-        kwargs["compile_config"] = _compile_config
+        kwargs["compile_config"] = _compile_config if cache_implementation is not None else None
     pass
 
     try:
@@ -310,6 +313,19 @@ def from_pretrained(
             bnb_compute_dtype = torch.float16
             do_forced_float32 = True
         pass
+
+        # Check for custom data-types
+        custom_datatype = None
+        correct_dtype = None
+        if os.environ.get("UNSLOTH_FORCE_CUSTOM_DTYPE", "") != "":
+            custom_datatype = os.environ["UNSLOTH_FORCE_CUSTOM_DTYPE"]
+            assert custom_datatype.count(";") == 1
+            bnb_compute_dtype, custom_datatype = custom_datatype.split(";", 1)
+            dtype = torch.float32
+            bnb_compute_dtype = eval(bnb_compute_dtype)
+            correct_dtype = bnb_compute_dtype
+        pass
+
         # Stop SDPA for some archs like Pixtral / Mistral3
         if not ("attn_implementation" in kwargs):
             kwargs["attn_implementation"] = "sdpa"
@@ -374,12 +390,18 @@ def from_pretrained(
         # Return old flag
         os.environ["HF_HUB_ENABLE_HF_TRANSFER"] = old_hf_transfer
 
+        # Edit data-types
+        if custom_datatype is not None:
+            for name, module in model.named_modules():
+                exec(custom_datatype)
+        pass
+
         # Counteract saved tokenizers
         tokenizer_name = model_name if tokenizer_name is None else tokenizer_name
         is_vlm = (auto_model is AutoModelForVision2Seq)
         is_whisper = (whisper_language is not None and whisper_task is not None)
         auto_processor = AutoProcessor if (is_vlm or is_whisper) else AutoTokenizer
-        if whisper_language and whisper_task:
+        if (whisper_language and whisper_task) or auto_model.__name__.endswith("ForConditionalGeneration"):
            tokenizer = auto_processor.from_pretrained(
                 tokenizer_name,
                 padding_side = "right",
@@ -415,6 +437,7 @@ def from_pretrained(
             downcast_rope = False,
             fix_embeddings = False,
             do_forced_float32 = do_forced_float32,
+            correct_dtype = correct_dtype,
         )
         model, tokenizer = patch_tokenizer(model, tokenizer)
         model = post_patch_loss_function(model)