Text Classification
Transformers
TensorBoard
Safetensors
English
distilbert
sentiment-analysis
twitter
nlp
sentiment140
Stanford
Egypt
Ain shams university
Hatem Moushir
Eval Results (legacy)
text-embeddings-inference
Instructions to use HatemMoushir/sentiment140-distilbert-hatem with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HatemMoushir/sentiment140-distilbert-hatem with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HatemMoushir/sentiment140-distilbert-hatem")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HatemMoushir/sentiment140-distilbert-hatem") model = AutoModelForSequenceClassification.from_pretrained("HatemMoushir/sentiment140-distilbert-hatem", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from HatemMoushir/sentiment140-distilbert-hatem: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/HatemMoushir/sentiment140-distilbert-hatem/resolve/main/tokenizer.json
- Command line
-
hf download hf://HatemMoushir/sentiment140-distilbert-hatem/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/HatemMoushir/sentiment140-distilbert-hatem/resolve/main/tokenizer.json
712 kB
File too large to display, you can check the raw version instead.