Text Classification
Transformers
Safetensors
English
distilbert
sentiment-analysis
text-embeddings-inference
Instructions to use ganesh435/my-first-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ganesh435/my-first-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ganesh435/my-first-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ganesh435/my-first-model") model = AutoModelForSequenceClassification.from_pretrained("ganesh435/my-first-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("ganesh435/my-first-model")
model = AutoModelForSequenceClassification.from_pretrained("ganesh435/my-first-model", device_map="auto")Quick Links
my-first-model
This is my first Hugging Face model.
Model Description
This model is based on DistilBERT and performs sentiment analysis.
How to use
from transformers import pipeline
classifier = pipeline("sentiment-analysis", model="ganesh435/my-first-model") classifier("I love learning AI with Hugging Face!")
Notes
This model was uploaded for learning purposes.
- Downloads last month
- 2
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ganesh435/my-first-model")