model=AutoModel.from_pretrained(model_type)# new tokensnew_tokens=["new_token"]# check if the tokens are already in the vocabularynew_tokens=set(new_tokens)-set(tokenizer.vocab.keys())# add the tokens to the tokenizer vocabularytokenizer.add_tokens(list(new_tokens))# add new, random embed...
/myt5-base is not a local folder and is not a valid model identifier listed on 'https://huggingface.co/models' E If this is a private repository, make sure to pass a token having permission to this repo either by logging in with huggingface-cli login or by passing token=<your_token>...
🚨🚨 🚨🚨 [Tokenizer] attemp to fix add_token issues🚨🚨 🚨🚨#23909 Merged ArthurZuckermerged 268 commits intohuggingface:mainfromArthurZucker:fix-add-tokens Sep 18, 2023 +2,304−2,053 Changes from17 commits File filter
I use huggingface transformers build a new moe model, when I use AutoForCasualModel to load the model, there is no suitable model structure to load it, in this case, the parameter couldn't be load correctly. To evaluate the performance of this model, I have to add a new style model i...
经过初步调研发现在英文世界的大模型,预训练数据都来自互联网爬取的全网数据,在英文世界有 Common crawl 这样的组织来维护这类全网爬虫数据集;也有 huggingface 这种非常好的社区,组织起 NLP 领域的模型 datasets 分享。 而在中文世界,似乎没有特别公开的大规模语料数...
I think one application of this Tuner may be in loading new tokens, I am just nervous around baking that into the tuner, as that requires aligning the Tokenizer. I think we should assume that new token's have been created and we just need to update them. Happy for feedback here. ...
model: Name or path of the huggingface model to use. tokenizer: Name or path of the huggingface tokenizer to use. tokenizer_mode: Tokenizer mode. "auto" will use the fast tokenizer if available, and "slow" will always use the slow tokenizer. ...
If the new tokens are not in the vocabulary, they are added to it with indices starting from length of the current vocabulary. When possible, special tokens are already registered for provided pretrained models (ex: BertTokenizer cls_token is already registered to be '[CLS]' and XLM's one...
original_tokenizer, "mergeable_ranks") and self.original_tokenizer.mergeable_ranks else load_tiktoken_bpe(tiktoken_file) ) byte_encoder = bytes_to_unicode() def token_bytes_to_string(b): return "".join([byte_encoder[ord(char)] for char in b.decode("latin-1")]) merges = [] vocab...
args.tokenizer = args.model main(args)3 changes: 3 additions & 0 deletions 3 vllm/config.py Original file line numberDiff line numberDiff line change @@ -16,6 +16,7 @@ class ModelConfig: Args: model: Name or path of the huggingface model to use. tokenizer: Name or path of the ...