Text Classification
Transformers
PyTorch
TensorBoard
ONNX
Chinese
bert
Generated from Trainer
text-embeddings-inference
Instructions to use xqchq/test-trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xqchq/test-trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xqchq/test-trainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xqchq/test-trainer") model = AutoModelForSequenceClassification.from_pretrained("xqchq/test-trainer") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -14,10 +14,9 @@ language:
|
|
| 14 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 15 |
should probably proofread and complete it, then remove this comment. -->
|
| 16 |
|
| 17 |
-
# test-
|
| 18 |
|
| 19 |
-
This model is a fine-tuned version of [hfl/minirbt-h256](https://huggingface.co/hfl/minirbt-h256) on
|
| 20 |
-
dataset is use seamew/THUCNewsText
|
| 21 |
|
| 22 |
|
| 23 |
## Model description
|
|
|
|
| 14 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 15 |
should probably proofread and complete it, then remove this comment. -->
|
| 16 |
|
| 17 |
+
# test-trainer1
|
| 18 |
|
| 19 |
+
This model is a fine-tuned version of [hfl/minirbt-h256](https://huggingface.co/hfl/minirbt-h256) on seamew/THUCNewsText dataset.
|
|
|
|
| 20 |
|
| 21 |
|
| 22 |
## Model description
|