vbatts/llama.cpp
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fix: Apply proper paths for handling qwen

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teleprint-me 2024-05-08 01:17:07 -04:00
parent 670e1c373b
commit 69efb59853
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1 changed files with 14 additions and 9 deletions
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23
convert-hf-to-gguf-update.py
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@ -120,14 +120,21 @@ for model in models:
# model and repo urls are not the same # model and repo urls are not the same
# url = "https://huggingface.co/Qwen/Qwen-tokenizer/raw/main/tokenizer.json" # url = "https://huggingface.co/Qwen/Qwen-tokenizer/raw/main/tokenizer.json"
if name == "qwen": # qwen is an outlier and will raise a FileNotFoundError if name == "qwen": # qwen is an outlier and will raise a FileNotFoundError
# fetch the qwen tokenizer # override the tokenizer path
model_tokenizer_path = f"{model_name_or_path}/qwen.tiktoken"
# fetch the qwens BPE tokenizer
download_file_with_auth( download_file_with_auth(
url="https://huggingface.co/Qwen/Qwen-tokenizer/raw/main/tokenizer.json", url="https://huggingface.co/Qwen/Qwen-7B/raw/main/qwen.tiktoken",
token=token, token=token,
save_path=model_tokenizer_path save_path=model_tokenizer_path
) )
else: # Et tu, Brute? # fetch qwens tokenizer script; this is required.
# Get the models tokenizer download_file_with_auth(
url="https://huggingface.co/Qwen/Qwen-7B/raw/main/tokenization_qwen.py",
token=token,
save_path=f"{model_name_or_path}/tokenization_qwen.py"
)
else: # Get the models tokenizer
download_file_with_auth( download_file_with_auth(
url=f"{url_main}/tokenizer.json", url=f"{url_main}/tokenizer.json",
token=token, token=token,
@ -177,8 +184,7 @@ for model in models:
if tokt == TOKENIZER_TYPE.SPM: if tokt == TOKENIZER_TYPE.SPM:
continue continue
# create the tokenizer tokenizer = AutoTokenizer.from_pretrained(f"models/tokenizers/{name}", trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained(model_name_or_path)
chktok = tokenizer.encode(chktxt) chktok = tokenizer.encode(chktxt)
chkhsh = sha256(str(chktok).encode()).hexdigest() chkhsh = sha256(str(chktok).encode()).hexdigest()
@ -314,8 +320,7 @@ for model in models:
name = model["name"] name = model["name"]
tokt = model["tokt"] tokt = model["tokt"]
# create the tokenizer tokenizer = AutoTokenizer.from_pretrained(f"models/tokenizers/{name}")
tokenizer = AutoTokenizer.from_pretrained(model_name_or_path)
with open(f"models/ggml-vocab-{name}.gguf.inp", "w", encoding="utf-8") as f: with open(f"models/ggml-vocab-{name}.gguf.inp", "w", encoding="utf-8") as f:
for text in tests: for text in tests:
@ -336,7 +341,7 @@ shscript = "#!/usr/bin/env bash\n\n"
for model in models: for model in models:
name = model["name"] name = model["name"]
tmpline = f"python3 convert-hf-to-gguf.py {model_name_or_path}/ --outfile models/ggml-vocab-{name}.gguf --vocab-only\n" tmpline = f"python3 convert-hf-to-gguf.py models/tokenizers/{name} --outfile models/ggml-vocab-{name}.gguf --vocab-only\n"
shscript += tmpline shscript += tmpline
logging.info(tmpline.strip()) logging.info(tmpline.strip())