Token Classification
Transformers
PyTorch
Safetensors
English
roberta
Instagram
NER
Named Entity Recognition
Food Entity Extraction
Social Media
Informal text
RoBERTa
Instructions to use Dizex/InstaFoodRoBERTa-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dizex/InstaFoodRoBERTa-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Dizex/InstaFoodRoBERTa-NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Dizex/InstaFoodRoBERTa-NER") model = AutoModelForTokenClassification.from_pretrained("Dizex/InstaFoodRoBERTa-NER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
bcd71e1
1
Parent(s): 784b5fb
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (28d7cc7c44a813604cc79c8f5a12c22633d97e0e)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:77b189fb6a58143aea1d41f5eccdfed70c9d42b89b506450294fca8877fc0674
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