ExternalVendorCode/whisper.cpp
1
0
Fork 0
mirror of https://github.com/ggerganov/whisper.cpp.git synced 2024-12-20 05:07:52 +00:00
Code Issues Actions Packages Projects Releases Wiki Activity

models : simplify the conversion script

Browse Source 
"transformers" dependency is not actually needed
This commit is contained in:
Georgi Gerganov 2022-11-16 19:21:43 +02:00
parent 55a0e1a64e
commit e70e5c8b53
No known key found for this signature in database
GPG Key ID: 449E073F9DC10735
1 changed files with 23 additions and 23 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

46
models/convert-pt-to-ggml.py
View File

@ -40,8 +40,8 @@ import code
import torch
import numpy as np
from transformers import GPTJForCausalLM
from transformers import GPT2TokenizerFast
#from transformers import GPTJForCausalLM
#from transformers import GPT2TokenizerFast
# ref: https://github.com/openai/whisper/blob/8cf36f3508c9acd341a45eb2364239a3d81458b9/whisper/tokenizer.py#L10-L110
LANGUAGES = {
@ -146,25 +146,25 @@ LANGUAGES = {
"su": "sundanese",
}
# ref: https://github.com/openai/whisper/blob/8cf36f3508c9acd341a45eb2364239a3d81458b9/whisper/tokenizer.py#L273-L292
def build_tokenizer(path_to_whisper_repo: str, name: str = "gpt2"):
os.environ["TOKENIZERS_PARALLELISM"] = "false"
path = os.path.join(path_to_whisper_repo, "whisper/assets", name)
tokenizer = GPT2TokenizerFast.from_pretrained(path)
specials = [
"<|startoftranscript|>",
*[f"<|{lang}|>" for lang in LANGUAGES.keys()],
"<|translate|>",
"<|transcribe|>",
"<|startoflm|>",
"<|startofprev|>",
"<|nocaptions|>",
"<|notimestamps|>",
]
tokenizer.add_special_tokens(dict(additional_special_tokens=specials))
return tokenizer
## ref: https://github.com/openai/whisper/blob/8cf36f3508c9acd341a45eb2364239a3d81458b9/whisper/tokenizer.py#L273-L292
#def build_tokenizer(path_to_whisper_repo: str, name: str = "gpt2"):
# os.environ["TOKENIZERS_PARALLELISM"] = "false"
# path = os.path.join(path_to_whisper_repo, "whisper/assets", name)
# tokenizer = GPT2TokenizerFast.from_pretrained(path)
#
# specials = [
# "<|startoftranscript|>",
# *[f"<|{lang}|>" for lang in LANGUAGES.keys()],
# "<|translate|>",
# "<|transcribe|>",
# "<|startoflm|>",
# "<|startofprev|>",
# "<|nocaptions|>",
# "<|notimestamps|>",
# ]
#
# tokenizer.add_special_tokens(dict(additional_special_tokens=specials))
# return tokenizer
# ref: https://github.com/openai/gpt-2/blob/master/src/encoder.py
def bytes_to_unicode():
@ -224,12 +224,12 @@ with np.load(os.path.join(dir_whisper, "whisper/assets", "mel_filters.npz")) as
#code.interact(local=locals())
multilingual = hparams["n_vocab"] == 51865
tokenizer = build_tokenizer(dir_whisper, multilingual and "multilingual" or "gpt2")
dir_tokenizer = os.path.join(dir_whisper, "whisper/assets", multilingual and "multilingual" or "gpt2")
#tokenizer = build_tokenizer(dir_whisper, multilingual and "multilingual" or "gpt2")
#print(tokenizer)
#print(tokenizer.name_or_path)
#print(len(tokenizer.additional_special_tokens))
dir_tokenizer = tokenizer.name_or_path
# output in the same directory as the model
fname_out = dir_out + "/ggml-model.bin"