mlc-ai / mlc-ai/tokenizers-cpp
tokenizer for triton inference server
Open
Nobody has claimed this yet.
- Dominant language
- C++
- Stars
- 512
- Forks
- 132
- PR merge metrics
- No merged PRs in 30d
Description
hi,
Can this be used with triton inference server for huggingface setfit (https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2)?
here is what i currently do with python:
from transformers import AutoTokenizer
# Load model from HuggingFace Hub
tokenizer = AutoTokenizer.from_pretrained('sentence-transformers/all-MiniLM-L6-v2')
# Tokenize sentences
encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt')
Thanks,
Gerald
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reviewing the repository's documented tokenizer API and examples, then compare them with the Python AutoTokenizer usage and the all-MiniLM-L6-v2 model named in the issue. Done means establishing whether this model and Triton inference-server workflow are supported, or documenting the missing compatibility requirements.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- cpp, huggingface, python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100