Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use MelikeErdogan/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MelikeErdogan/output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MelikeErdogan/output")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MelikeErdogan/output") model = AutoModelForSequenceClassification.from_pretrained("MelikeErdogan/output") - Notebooks
- Google Colab
- Kaggle
Commit ·
084b93c
1
Parent(s): 78b4c32
Update README.md
Browse files
README.md
CHANGED
|
@@ -18,7 +18,7 @@ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingf
|
|
| 18 |
|
| 19 |
## Model description
|
| 20 |
|
| 21 |
-
This model gives the
|
| 22 |
|
| 23 |
|
| 24 |
## Intended uses & limitations
|
|
|
|
| 18 |
|
| 19 |
## Model description
|
| 20 |
|
| 21 |
+
This model gives the result of LABEL_1 if the given sentences are positive, and LABEL_0 if they are negative, together with the calculated probabality values.
|
| 22 |
|
| 23 |
|
| 24 |
## Intended uses & limitations
|