Instructions to use carblacac/ner-investing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use carblacac/ner-investing with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="carblacac/ner-investing")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("carblacac/ner-investing") model = AutoModelForTokenClassification.from_pretrained("carblacac/ner-investing") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:a20e9cef0b5931616ed75d91a08fdf050fd983ca313df4b1360021d8234e0cd6
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size 1109892772
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