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 ·
af4bca7
1
Parent(s): b67a30c
test pipline.py
Browse files- pipline.py +7 -0
pipline.py
ADDED
|
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
from transformers import distilbert-base-cased-distilled-squad
|
| 2 |
+
|
| 3 |
+
@pipeline("Question Answering")
|
| 4 |
+
def to_task(inputs):
|
| 5 |
+
return "this is a test."
|
| 6 |
+
# model = distilbert-base-cased-distilled-squad.from_pretrained(".")
|
| 7 |
+
# return model(inputs)
|