Comments (1)
Hi @dsindex. We are currently in the process of updating transformers
with the last version of tokenizers
so this is totally normal. You will be able to upgrade soon!
Also please note that tokenizers
being quite young, we sometimes introduce breaking changes, so having a specific version that can be used with transformers
lets us make sure everything keeps working for you.
from tokenizers.
Related Issues (20)
- tokenizers-linux-x64-musl is not found when running inside node apline docker
- `BertWordPieceTokenizer` not saving with `sep_token` marked HOT 2
- error: casting `&T` to `&mut T` is undefined behavior HOT 1
- Is it possible to pass a tokenizer from Python into Rust?
- Discrepancy Between GitHub Release and NPM Package Version & Missing Dependencies HOT 1
- Deepseeker model completely loses performance after using tokenizer.add_tokens(special_tokens)
- Unsound use of unsafe in `src/utils/parallelism.rs`
- LLamaTokenizer with `use_fast=True` / and `use_fast=False` causing memory leak when used with multiprocessing / `dataset.map(num_proc)` HOT 1
- StripAccents doesn't work
- Issue in installing rudalle on google colab, !pip install rudalle
- Extended vocab tokenizer merging text into a single string without spaces while decoding
- offline installation HOT 1
- Failing to build bindings with 0.19.1 HOT 1
- Python Binding: Tokenizer.from_file() cannot parse JSON file of tokens HOT 1
- Treatment of hyphenated words
- Cross-compilation fails for custom target
- Breaking changes in v0.19.1 for tiktoken/llama3 HOT 3
- BPE Trainer doesn't respect the `vocab_size` parameter when dataset size is increased HOT 1
- UnigramTrainer: byte_fallback is false.
- Tokens Removed from Trained Custom BPE Tokenizer
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