Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use ViktorDo/SciBERT-POWO_Lifecycle_Finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ViktorDo/SciBERT-POWO_Lifecycle_Finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ViktorDo/SciBERT-POWO_Lifecycle_Finetuned")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ViktorDo/SciBERT-POWO_Lifecycle_Finetuned") model = AutoModelForSequenceClassification.from_pretrained("ViktorDo/SciBERT-POWO_Lifecycle_Finetuned") - 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:ef144e81bd093a0233ea9ccf916528d6d38535f8aec38fd6226321f2bcdb5b01
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size 439707728
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