Update README.md

README.md

@@ -2,7 +2,7 @@
 tags: autotrain
 language: tr
 widget:
-- text: "I love AutoTrain 🤗"
+- text: "Bu ürün gerçekten güzel çıktı"
 datasets:
 - emre/autotrain-data-turkish-sentiment-analysis
 co2_eq_emissions: 120.82460124309924
@@ -34,7 +34,7 @@ co2_eq_emissions: 120.82460124309924
 You can use cURL to access this model:
 
 ```
-$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/models/emre/autotrain-turkish-sentiment-analysis-870727732
+$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "Bu ürün gerçekten güzel çıktı"}' https://api-inference.huggingface.co/models/emre/turkish-sentiment-analysis
 ```
 
 Or Python API:
@@ -42,11 +42,11 @@ Or Python API:
 ```
 from transformers import AutoModelForSequenceClassification, AutoTokenizer
 
-model = AutoModelForSequenceClassification.from_pretrained("emre/autotrain-turkish-sentiment-analysis-870727732", use_auth_token=True)
+model = AutoModelForSequenceClassification.from_pretrained("emre/turkish-sentiment-analysis", use_auth_token=True)
 
-tokenizer = AutoTokenizer.from_pretrained("emre/autotrain-turkish-sentiment-analysis-870727732", use_auth_token=True)
+tokenizer = AutoTokenizer.from_pretrained("emre/turkish-sentiment-analysis", use_auth_token=True)
 
-inputs = tokenizer("I love AutoTrain", return_tensors="pt")
+inputs = tokenizer("Bu ürün gerçekten güzel çıktı", return_tensors="pt")
 
 outputs = model(**inputs)
 ```