Text Classification
Transformers
Safetensors
distilbert
Sentiment Analysis
Text Classification
BERT
Yelp Reviews
Fine-tuned
text-embeddings-inference
Instructions to use kmack/YELP-Review_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kmack/YELP-Review_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kmack/YELP-Review_Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kmack/YELP-Review_Classifier") model = AutoModelForSequenceClassification.from_pretrained("kmack/YELP-Review_Classifier") - Notebooks
- Google Colab
- Kaggle
Upload model.safetensors with huggingface_hub
Browse files- model.safetensors +3 -0
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:71d5c22cc7d46409ea2612de3dee75b0659364d4b226da807247042dd58e618d
|
| 3 |
+
size 267841796
|