Instructions to use InstaDeepAI/segment_nt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use InstaDeepAI/segment_nt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="InstaDeepAI/segment_nt", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("InstaDeepAI/segment_nt", trust_remote_code=True) model = AutoModel.from_pretrained("InstaDeepAI/segment_nt", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from InstaDeepAI/segment_nt: direct link, hf CLI and curl.
- Browser
- Download file 129 Bytes
-
https://huggingface.co/InstaDeepAI/segment_nt/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://InstaDeepAI/segment_nt/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/InstaDeepAI/segment_nt/resolve/main/tokenizer_config.json
129 Bytes
| { | |
| "clean_up_tokenization_spaces": true, | |
| "eos_token": null, | |
| "model_max_length": 2048, | |
| "tokenizer_class": "EsmTokenizer" | |
| } | |