Token Classification
Transformers
PyTorch
TensorFlow
Rust
Safetensors
OpenVINO
English
distilbert
Eval Results (legacy)
Instructions to use wbq/model-api-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wbq/model-api-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="wbq/model-api-test")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("wbq/model-api-test") model = AutoModelForTokenClassification.from_pretrained("wbq/model-api-test") - Notebooks
- Google Colab
- Kaggle
BiqiangWang commited on
Commit ·
53dd3ed
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Parent(s): af4bca7
Revert "test pipline.py"
Browse filesThis reverts commit af4bca713561a1688c977f0df32bc576a30cf2ab.
- pipline.py +0 -7
pipline.py
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from transformers import distilbert-base-cased-distilled-squad
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@pipeline("Question Answering")
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def to_task(inputs):
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return "this is a test."
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# model = distilbert-base-cased-distilled-squad.from_pretrained(".")
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# return model(inputs)
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