Text Classification
Transformers
Safetensors
PyTorch
English
distilbert
sarcasm
reddit
text-embeddings-inference
Instructions to use tmrcnl/SarcasmRewardModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tmrcnl/SarcasmRewardModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tmrcnl/SarcasmRewardModel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tmrcnl/SarcasmRewardModel") model = AutoModelForSequenceClassification.from_pretrained("tmrcnl/SarcasmRewardModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4e235ca62c9cd467fe0536f66bdce3ff9cfc4db944b33e41262fcb2ddbf4416
- Size of remote file:
- 5.97 kB
- SHA256:
- 4af2eca2465b6b27a5d50fab35c4cca5afd9fae403449ce3bac6ff61fe77d297
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.