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 ·
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Parent(s): a83ec20
test update config.json
Browse files- README.md +0 -1
- config.json +1 -0
README.md
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---
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language: en
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license: apache-2.0
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pipline_tag: text-classification
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datasets:
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- squad
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metrics:
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---
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language: en
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license: apache-2.0
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datasets:
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- squad
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metrics:
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config.json
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{
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"activation": "gelu",
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"architectures": [
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"DistilBertForQuestionAnswering"
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],
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"attention_dropout": 0.1,
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{
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"activation": "gelu",
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"architectures": [
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"DistilBertForTokenClassification",
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"DistilBertForQuestionAnswering"
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],
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"attention_dropout": 0.1,
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