Instructions to use rezaFarsh/binary_persian_sentiment_analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rezaFarsh/binary_persian_sentiment_analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rezaFarsh/binary_persian_sentiment_analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rezaFarsh/binary_persian_sentiment_analysis") model = AutoModelForSequenceClassification.from_pretrained("rezaFarsh/binary_persian_sentiment_analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 19
Browse files- model.safetensors +1 -1
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1883737480
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:439e2f0a14d75b105cb63ac3c20ff293d706dc23cdfcfc2feb293c35af468198
|
| 3 |
size 1883737480
|