llama-3 bug fixes (#429)
* Fix prompt * Update chat_templates.py * fix_untrained_tokens * Update llama.py * add tokens * Update _utils.py * Update tokenizer_utils.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * pad_token * Update chat_templates.py * Update chat_templates.py * tokenizer * Update save.py * Update chat_templates.py * Update chat_templates.py * patch tokenizer padding * Update tokenizer_utils.py * Update save.py * Fix: loading models with resized vocabulary (#377) * new: vocab resize on load * new: gitignore * GGUF fix * Readme (#390) * Update README.md * Update README.md --------- Co-authored-by: Michael Han <107991372+shimmyshimmer@users.noreply.github.com> * Update README.md * Delete .gitignore * Phi-3 * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Fix reserved tokens * Update save.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update chat_templates.py * Update save.py * Update _utils.py * Update chat_templates.py --------- Co-authored-by: Igor Kilbas <whitemarsstudios@gmail.com> Co-authored-by: Michael Han <107991372+shimmyshimmer@users.noreply.github.com>
This commit is contained in:
Daniel Han
GitHub
parent
a93a885c28
commit
4211cc0140
3 changed files with 103 additions and 18 deletions
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@ -266,6 +266,20 @@ llama3_template_eos_token = "eos_token"
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CHAT_TEMPLATES["llama-3"] = (llama3_template, llama3_template_eos_token,)
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# Phi-3
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phi3_template = \
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"{{ bos_token }}"\
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"{% for message in messages %}"\
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"{% if (message['role'] == 'user') %}"\
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"{{'<|user|>' + '\n' + message['content'] + '<|end|>' + '\n' + '<|assistant|>' + '\n'}}"\
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"{% elif (message['role'] == 'assistant') %}"\
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"{{message['content'] + '<|end|>' + '\n'}}"\
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"{% endif %}"\
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"{% endfor %}"
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phi3_template_eos_token = "<|end|>"
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CHAT_TEMPLATES["phi-3"] = (phi3_template, phi3_template_eos_token,)
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def get_chat_template(
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tokenizer,
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chat_template = "chatml",
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@ -595,4 +609,12 @@ def test_chat_templates():
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correct_tokenizer.chat_template = template
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our_prompt = correct_tokenizer.apply_chat_template(messages, tokenize = False, add_generation_prompt = True)
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assert(correct_prompt == our_prompt)
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# Phi-3
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template = phi3_template
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correct_tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3-mini-4k-instruct")
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correct_prompt = correct_tokenizer.apply_chat_template(messages, tokenize = False, add_generation_prompt = True)
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correct_tokenizer.chat_template = template
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our_prompt = correct_tokenizer.apply_chat_template(messages, tokenize = False, add_generation_prompt = True)
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assert(correct_prompt == our_prompt)
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pass
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@ -144,24 +144,60 @@ pass
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def patch_tokenizer(model, tokenizer):
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"""
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Phi3's pad_token isn't set. We set it to <|placeholder...
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Llama-3 is <|reserved...
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Llama-2 is <unk>
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Check if pad_token is not the same as eos_token otherwise the loss will ignore it!!
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Fixes https://github.com/unslothai/unsloth/issues/5
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"""
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possible_reserved_tokens = ("<|reserved", "<|placeholder",)
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if model is not None:
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model.config.update({"unsloth_version" : __version__})
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if not hasattr(tokenizer, "pad_token") or tokenizer.pad_token is None:
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# Fixes https://github.com/unslothai/unsloth/issues/5
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if hasattr(tokenizer, "unk_token") and tokenizer.unk_token is not None:
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tokenizer.add_special_tokens({"pad_token" : tokenizer.unk_token})
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tokenizer.pad_token = tokenizer.unk_token
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else:
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name = model.config._name_or_path if model is not None else "Model"
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logger.warning_once(
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f"{name} does not have a padding or unknown token!\n"\
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f"Will use the EOS token of id {tokenizer.eos_token_id} as padding."
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bad_pad_token = False
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if hasattr(tokenizer, "pad_token") and tokenizer.pad_token is not None:
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# Check if pad_token is not the same as eos_token otherwise the loss will ignore it!!
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bad_pad_token = tokenizer.eos_token == tokenizer.pad_token
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elif hasattr(tokenizer, "pad_token") and tokenizer.pad_token is None:
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bad_pad_token = True
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else:
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bad_pad_token = False
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pass
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if bad_pad_token:
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# Find a better pad token
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added_tokens = [str(x) for x in tokenizer.added_tokens_decoder.values()]
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possible_pad_token = None
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for added_token in added_tokens[::-1]:
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if added_token.startswith(possible_reserved_tokens):
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possible_pad_token = added_token
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break
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pass
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pass
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if possible_pad_token is None:
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# Try unk_token
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possible_pad_token = tokenizer.unk_token
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pass
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if possible_pad_token is None:
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# Failure!!
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raise RuntimeError(
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"Unsloth: Tokenizer's pad_token cannot be = eos_token, and we couldn't find a\n"\
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"replacement of either <|reserved... or <|placeholder..."
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)
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assert(hasattr(tokenizer, "eos_token"))
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tokenizer.add_special_tokens({"pad_token" : tokenizer.eos_token})
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tokenizer.pad_token = tokenizer.eos_token
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pass
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name = model.config._name_or_path if model is not None else "Model"
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logger.warning_once(
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f"{name} does not have a padding token! Will use pad_token = {possible_pad_token}."
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)
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# Edit pad_token
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tokenizer.add_special_tokens({"pad_token" : possible_pad_token})
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tokenizer.pad_token = possible_pad_token
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if model is not None:
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config = model.config.update({"pad_token_id" : tokenizer.eos_token_id})
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config = model.config.update({"pad_token_id" : tokenizer.pad_token_id})
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pass
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return model, tokenizer
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pass
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@ -18,6 +18,7 @@ from peft.tuners.lora import Linear as Peft_Linear
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from typing import Optional, Callable, Union, List
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import torch
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import os
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import shutil
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import pickle
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import gc
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from transformers.models.llama.modeling_llama import logger
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@ -87,6 +88,24 @@ def print_quantization_methods():
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pass
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def check_if_sentencepiece_model(model, temporary_location = "_unsloth_sentencepiece_temp"):
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if not hasattr(model, "_saved_temp_tokenizer"): return False
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temp_tokenizer = model._saved_temp_tokenizer
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sentencepiece_model = False
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file_location = f"{temporary_location}/{temp_tokenizer.name_or_path}"
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if not os.path.exists(file_location):
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os.makedirs(file_location)
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pass
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temp_tokenizer.save_pretrained(file_location)
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if os.path.isfile(f"{file_location}/tokenizer.model"):
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sentencepiece_model = True
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pass
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shutil.rmtree(file_location)
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return sentencepiece_model
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pass
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def _free_cached_model(model):
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from huggingface_hub import scan_cache_dir
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cached_repos = list(scan_cache_dir().repos)
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@ -840,6 +859,7 @@ pass
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def save_to_gguf(
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model_type : str,
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is_sentencepiece : bool = False,
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model_directory : str = "unsloth_finetuned_model",
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quantization_method : str = "fast_quantized",
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first_conversion : str = "f16",
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@ -856,7 +876,8 @@ def save_to_gguf(
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# Careful convert.py is only for Llama / Mistral based archs
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use_fast_convert = False
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if model_type == "llama": use_fast_convert = True
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if not is_sentencepiece: use_fast_convert = False # Llama-3
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elif model_type == "llama": use_fast_convert = True
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elif model_type == "mistral": use_fast_convert = True
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pass
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logger.warning_once(f"Unsloth: Converting {model_type} model. Can use fast conversion = {use_fast_convert}.")
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@ -951,7 +972,7 @@ def save_to_gguf(
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f"--outtype {first_conversion} --concurrency {n_cpus}"
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else:
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# Need to fix convert-hf-to-gguf.py for some models!
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_fix_gemma_gguf()
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# _fix_gemma_gguf()
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command = f"python llama.cpp/convert-hf-to-gguf.py {model_directory} "\
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f"--outfile {final_location} "\
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@ -1353,7 +1374,10 @@ def unsloth_save_pretrained_gguf(
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gc.collect()
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model_type = self.config.model_type
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file_location = save_to_gguf(model_type, new_save_directory, quantization_method, first_conversion, makefile)
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is_sentencepiece_model = check_if_sentencepiece_model(self)
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file_location = save_to_gguf(model_type, is_sentencepiece_model,
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new_save_directory, quantization_method, first_conversion, makefile,
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)
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if push_to_hub:
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print("Unsloth: Uploading GGUF to Huggingface Hub...")
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@ -1473,7 +1497,10 @@ def unsloth_push_to_hub_gguf(
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gc.collect()
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model_type = self.config.model_type
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file_location = save_to_gguf(model_type, new_save_directory, quantization_method, first_conversion, makefile)
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is_sentencepiece_model = check_if_sentencepiece_model(self)
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file_location = save_to_gguf(model_type, is_sentencepiece_model,
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new_save_directory, quantization_method, first_conversion, makefile,
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)
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print("Unsloth: Uploading GGUF to Huggingface Hub...")
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username = upload_to_huggingface(
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