Token Classification
Transformers
PyTorch
English
roberta
keyphrase-extraction
Eval Results (legacy)
Instructions to use ml6team/keyphrase-extraction-kbir-inspec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ml6team/keyphrase-extraction-kbir-inspec with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ml6team/keyphrase-extraction-kbir-inspec")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ml6team/keyphrase-extraction-kbir-inspec") model = AutoModelForTokenClassification.from_pretrained("ml6team/keyphrase-extraction-kbir-inspec") - Notebooks
- Google Colab
- Kaggle
Can this model be finetuned on other custom domain data - still within the larger scientific/IT/comp sci domain
#2
by shershah11 - opened
Is there a notebook to finetune this?
Just realized this is finetune on KBIR , which builds on top of ROBERTA.
https://huggingface.co/bloomberg/KBIR.
Bloomberg developers mentioned : As mentioned above since KBIR is built on top of the RoBERTa architecture, it is compatible with any AutoModel setting that RoBERTa is also compatible with.
Sorry for the spam - feel free to delete the discussion
For anyone else looking to Finetune, the KBIR model can be finetuned using standard huggingface/Roberta API.
shershah11 changed discussion status to closed