llama-3 bug fixes

unsloth/chat_templates.py

@@ -266,6 +266,20 @@
 CHAT_TEMPLATES["llama-3"] = (llama3_template, llama3_template_eos_token,)
 
 
+# Phi-3
+phi3_template = \
+    "{{ bos_token }}"\
+    "{% for message in messages %}"\
+        "{% if (message['role'] == 'user') %}"\
+            "{{'<|user|>' + '\n' + message['content'] + '<|end|>' + '\n' + '<|assistant|>' + '\n'}}"\
+        "{% elif (message['role'] == 'assistant') %}"\
+            "{{message['content'] + '<|end|>' + '\n'}}"\
+        "{% endif %}"\
+    "{% endfor %}"
+phi3_template_eos_token = "<|end|>"
+CHAT_TEMPLATES["phi-3"] = (phi3_template, phi3_template_eos_token,)
+
+
 def get_chat_template(
     tokenizer,
     chat_template = "chatml",
@@ -595,4 +609,12 @@ def test_chat_templates():
     correct_tokenizer.chat_template = template
     our_prompt = correct_tokenizer.apply_chat_template(messages, tokenize = False, add_generation_prompt = True)
     assert(correct_prompt == our_prompt)
+
+    # Phi-3
+    template = phi3_template
+    correct_tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3-mini-4k-instruct")
+    correct_prompt = correct_tokenizer.apply_chat_template(messages, tokenize = False, add_generation_prompt = True)
+    correct_tokenizer.chat_template = template
+    our_prompt = correct_tokenizer.apply_chat_template(messages, tokenize = False, add_generation_prompt = True)
+    assert(correct_prompt == our_prompt)
 pass

unsloth/models/_utils.py

@@ -144,24 +144,60 @@ def make_inputs_require_grad(module, input, output):
 
 
 def patch_tokenizer(model, tokenizer):
+    """
+        Phi3's pad_token isn't set. We set it to <|placeholder...
+        Llama-3 is <|reserved...
+        Llama-2 is <unk>
+        Check if pad_token is not the same as eos_token otherwise the loss will ignore it!!
+        Fixes https://github.com/unslothai/unsloth/issues/5
+    """
+    possible_reserved_tokens = ("<|reserved", "<|placeholder",)
+
     if model is not None:
         model.config.update({"unsloth_version" : __version__})
-    if not hasattr(tokenizer, "pad_token") or tokenizer.pad_token is None:
-        # Fixes https://github.com/unslothai/unsloth/issues/5
-        if hasattr(tokenizer, "unk_token") and tokenizer.unk_token is not None:
-            tokenizer.add_special_tokens({"pad_token" : tokenizer.unk_token})
-            tokenizer.pad_token = tokenizer.unk_token
-        else:
-            name = model.config._name_or_path if model is not None else "Model"
-            logger.warning_once(
-                f"{name} does not have a padding or unknown token!\n"\
-                f"Will use the EOS token of id {tokenizer.eos_token_id} as padding."
+
+    bad_pad_token = False
+    if hasattr(tokenizer, "pad_token") and tokenizer.pad_token is not None:
+        # Check if pad_token is not the same as eos_token otherwise the loss will ignore it!!
+        bad_pad_token = tokenizer.eos_token == tokenizer.pad_token
+    elif hasattr(tokenizer, "pad_token") and tokenizer.pad_token is None:
+        bad_pad_token = True
+    else:
+        bad_pad_token = False
+    pass
+
+    if bad_pad_token:
+        # Find a better pad token
+        added_tokens = [str(x) for x in tokenizer.added_tokens_decoder.values()]
+        possible_pad_token = None
+        for added_token in added_tokens[::-1]:
+            if added_token.startswith(possible_reserved_tokens):
+                possible_pad_token = added_token
+                break
+            pass
+        pass
+        if possible_pad_token is None:
+            # Try unk_token
+            possible_pad_token = tokenizer.unk_token
+        pass
+        if possible_pad_token is None:
+            # Failure!!
+            raise RuntimeError(
+                "Unsloth: Tokenizer's pad_token cannot be = eos_token, and we couldn't find a\n"\
+                "replacement of either <|reserved... or <|placeholder..."
             )
-            assert(hasattr(tokenizer, "eos_token"))
-            tokenizer.add_special_tokens({"pad_token" : tokenizer.eos_token})
-            tokenizer.pad_token = tokenizer.eos_token
+        pass
+
+        name = model.config._name_or_path if model is not None else "Model"
+        logger.warning_once(
+            f"{name} does not have a padding token! Will use pad_token = {possible_pad_token}."
+        )
+
+        # Edit pad_token
+        tokenizer.add_special_tokens({"pad_token" : possible_pad_token})
+        tokenizer.pad_token = possible_pad_token
         if model is not None:
-            config = model.config.update({"pad_token_id" : tokenizer.eos_token_id})
+            config = model.config.update({"pad_token_id" : tokenizer.pad_token_id})
     pass
     return model, tokenizer
 pass

unsloth/save.py

@@ -18,6 +18,7 @@
 from typing import Optional, Callable, Union, List
 import torch
 import os
+import shutil
 import pickle
 import gc
 from transformers.models.llama.modeling_llama import logger
@@ -87,6 +88,24 @@ def print_quantization_methods():
 pass
 
 
+def check_if_sentencepiece_model(model, temporary_location = "_unsloth_sentencepiece_temp"):
+    if not hasattr(model, "_saved_temp_tokenizer"): return False
+
+    temp_tokenizer = model._saved_temp_tokenizer
+    sentencepiece_model = False
+    file_location = f"{temporary_location}/{temp_tokenizer.name_or_path}"
+    if not os.path.exists(file_location):
+        os.makedirs(file_location)
+    pass
+    temp_tokenizer.save_pretrained(file_location)
+    if os.path.isfile(f"{file_location}/tokenizer.model"):
+        sentencepiece_model = True
+    pass
+    shutil.rmtree(file_location)
+    return sentencepiece_model
+pass
+
+
 def _free_cached_model(model):
     from huggingface_hub import scan_cache_dir
     cached_repos = list(scan_cache_dir().repos)
@@ -840,6 +859,7 @@ def _fix_gemma_gguf():
 
 def save_to_gguf(
     model_type           : str,
+    is_sentencepiece     : bool = False,
     model_directory      : str = "unsloth_finetuned_model",
     quantization_method  : str = "fast_quantized",
     first_conversion     : str = "f16",
@@ -856,7 +876,8 @@ def save_to_gguf(
 
     # Careful convert.py is only for Llama / Mistral based archs
     use_fast_convert = False
-    if   model_type == "llama":   use_fast_convert = True
+    if not is_sentencepiece:      use_fast_convert = False # Llama-3
+    elif model_type == "llama":   use_fast_convert = True
     elif model_type == "mistral": use_fast_convert = True
     pass
     logger.warning_once(f"Unsloth: Converting {model_type} model. Can use fast conversion = {use_fast_convert}.")
@@ -951,7 +972,7 @@ def save_to_gguf(
             f"--outtype {first_conversion} --concurrency {n_cpus}"
     else:
         # Need to fix convert-hf-to-gguf.py for some models!
-        _fix_gemma_gguf()
+        # _fix_gemma_gguf()
 
         command = f"python llama.cpp/convert-hf-to-gguf.py {model_directory} "\
             f"--outfile {final_location} "\
@@ -1353,7 +1374,10 @@ def unsloth_save_pretrained_gguf(
         gc.collect()
 
     model_type = self.config.model_type
-    file_location = save_to_gguf(model_type, new_save_directory, quantization_method, first_conversion, makefile)
+    is_sentencepiece_model = check_if_sentencepiece_model(self)
+    file_location = save_to_gguf(model_type, is_sentencepiece_model, 
+        new_save_directory, quantization_method, first_conversion, makefile,
+    )
 
     if push_to_hub:
         print("Unsloth: Uploading GGUF to Huggingface Hub...")
@@ -1473,7 +1497,10 @@ def unsloth_push_to_hub_gguf(
         gc.collect()
 
     model_type = self.config.model_type
-    file_location = save_to_gguf(model_type, new_save_directory, quantization_method, first_conversion, makefile)
+    is_sentencepiece_model = check_if_sentencepiece_model(self)
+    file_location = save_to_gguf(model_type, is_sentencepiece_model, 
+        new_save_directory, quantization_method, first_conversion, makefile,
+    )
 
     print("Unsloth: Uploading GGUF to Huggingface Hub...")
     username = upload_to_huggingface(