165 lines
6.9 KiB
Python
165 lines
6.9 KiB
Python
# Instructions:
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#
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# - Add a new model to the "models" list
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# - Run the script with your huggingface token:
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#
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# python3 convert-hf-to-gguf-update.py <huggingface_token>
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#
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# - Copy-paste the generated get_vocab_base_pre() function into convert-hf-to-gguf.py
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# - Update llama.cpp with the new pre-tokenizer if necessary
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#
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# TODO: generate tokenizer tests for llama.cpp
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#
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import os
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import requests
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import sys
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import json
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from hashlib import sha256
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from enum import IntEnum, auto
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class TOKENIZER_TYPE(IntEnum):
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SPM = auto()
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BPE = auto()
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WPM = auto()
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# TODO: this string has to exercise as much pre-tokenizer functionality as possible
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# will be updated with time - contributions welcome
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chktxt = '\n \n\n \n\n\n \t \t\t \t\n \n \n \n \n🚀 (normal) 😶🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天～ ------======= нещо на Български what\'s \'\'\'\'\'\'```````\"\"\"\"......!!!!!!??????'
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if len(sys.argv) == 2:
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token = sys.argv[1]
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else:
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print("Usage: python convert-hf-to-gguf-update.py <huggingface_token>")
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sys.exit(1)
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# TODO: add models here, base models preferred
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models = [
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{ "name": "llama-v2", "tokt": TOKENIZER_TYPE.SPM, "repo": "https://huggingface.co/meta-llama/Llama-2-7b-hf", },
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{ "name": "llama-v3", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/meta-llama/Meta-Llama-3-8B", },
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{ "name": "deepseek-llm", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/deepseek-ai/deepseek-llm-7b-base", },
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{ "name": "deepseek-coder", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-base", },
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{ "name": "falcon", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/tiiuae/falcon-7b", },
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{ "name": "bert-bge", "tokt": TOKENIZER_TYPE.WPM, "repo": "https://huggingface.co/BAAI/bge-small-en-v1.5", },
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]
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# make directory "models/tokenizers" if it doesn't exist
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if not os.path.exists("models/tokenizers"):
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os.makedirs("models/tokenizers")
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def download_file_with_auth(url, token, save_path):
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headers = {"Authorization": f"Bearer {token}"}
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response = requests.get(url, headers=headers)
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if response.status_code == 200:
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with open(save_path, 'wb') as f:
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f.write(response.content)
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print("File downloaded successfully.")
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else:
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print(f"Failed to download file. Status code: {response.status_code}")
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for model in models:
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name = model["name"]
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repo = model["repo"]
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tokt = model["tokt"]
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if not os.path.exists(f"models/tokenizers/{name}"):
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os.makedirs(f"models/tokenizers/{name}")
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else:
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print(f"Directory models/tokenizers/{name} already exists - skipping")
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continue
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print(f"Downloading {name} to models/tokenizers/{name}")
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url = f"{repo}/raw/main/tokenizer.json"
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save_path = f"models/tokenizers/{name}/tokenizer.json"
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download_file_with_auth(url, token, save_path)
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if tokt == TOKENIZER_TYPE.SPM:
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url = f"{repo}/resolve/main/tokenizer.model"
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save_path = f"models/tokenizers/{name}/tokenizer.model"
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download_file_with_auth(url, token, save_path)
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url = f"{repo}/raw/main/tokenizer_config.json"
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save_path = f"models/tokenizers/{name}/tokenizer_config.json"
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download_file_with_auth(url, token, save_path)
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# generate the source code for the convert-hf-to-gguf.py:get_vocab_base_pre() function:
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# TODO: auto-update convert-hf-to-gguf.py with the generated function
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src_ifs = ""
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for model in models:
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name = model["name"]
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tokt = model["tokt"]
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if tokt == TOKENIZER_TYPE.SPM:
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continue
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# create the tokenizer
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from transformers import AutoTokenizer
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tokenizer = AutoTokenizer.from_pretrained(f"models/tokenizers/{name}")
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chktok = tokenizer.encode(chktxt)
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chkhsh = sha256(str(chktok).encode()).hexdigest()
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print(f"model: {name}")
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print(f"tokt: {tokt}")
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print(f"repo: {model['repo']}")
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print(f"chktok: {chktok}")
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print(f"chkhsh: {chkhsh}")
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# print the "pre_tokenizer" content from the tokenizer.json
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with open(f"models/tokenizers/{name}/tokenizer.json", "r") as f:
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cfg = json.load(f)
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pre_tokenizer = cfg["pre_tokenizer"]
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print("pre_tokenizer: " + json.dumps(pre_tokenizer, indent=4))
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print(f"\n")
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src_ifs += f" if chkhsh == \"{chkhsh}\":\n"
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src_ifs += f" # ref: {model['repo']}\n"
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src_ifs += f" res = \"{name}\"\n"
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src_func = ""
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src_func += " def get_vocab_base_pre(self, tokenizer) -> str:\n"
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src_func += " # encoding this string and hashing the resulting tokens would (hopefully) give us a unique identifier that\n"
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src_func += " # is specific for the BPE pre-tokenizer used by the model\n"
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src_func += " # we will use this unique identifier to write a \"tokenizer.ggml.pre\" entry in the GGUF file which we can\n"
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src_func += " # use in llama.cpp to implement the same pre-tokenizer\n"
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src_func += "\n"
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src_func += f" chktxt = {repr(chktxt)}\n"
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src_func += "\n"
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src_func += " chktok = tokenizer.encode(chktxt)\n"
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src_func += " chkhsh = sha256(str(chktok).encode()).hexdigest()\n"
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src_func += "\n"
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src_func += " print(f\"chktok: {chktok}\")\n"
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src_func += " print(f\"chkhsh: {chkhsh}\")\n"
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src_func += "\n"
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src_func += " res = None\n"
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src_func += "\n"
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src_func += " # NOTE: if you get an error here, you need to add the model to the if-elif chain below\n"
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src_func += f"{src_ifs}\n"
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src_func += " if res is None:\n"
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src_func += " print( \"\\n\")\n"
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src_func += " print( \"**************************************************************************************\")\n"
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src_func += " print( \"** WARNING: The BPE pre-tokenizer was not recognized!\")\n"
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src_func += " print( \"** This means that it was not added yet or you are using an older version.\")\n"
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src_func += " print( \"** Check convert-hf-to-gguf-update.py and update it accordingly.\")\n"
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src_func += " print( \"**\")\n"
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src_func += " print(f\"** chkhsh: {chkhsh}\")\n"
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src_func += " print( \"**************************************************************************************\")\n"
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src_func += " print( \"\\n\")\n"
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src_func += " raise NotImplementedError(\"BPE pre-tokenizer was not recognized - update get_vocab_base_pre()\")\n"
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src_func += "\n"
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src_func += " print(f\"tokenizer.ggml.pre: {res}\")\n"
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src_func += " print(f\"chkhsh: {chkhsh}\")\n"
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src_func += "\n"
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src_func += " return res\n"
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print(src_func)
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print("\n")
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print("!!! Copy-paste the function above into convert-hf-to-gguf.py !!!")
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print("\n")
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