Zero-Shot Classification
Transformers
Safetensors
English
deberta-v2
text-classification
Politics
Twitter
Instructions to use mlburnham/deberta-v3-base-polistance-affect-v1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mlburnham/deberta-v3-base-polistance-affect-v1.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="mlburnham/deberta-v3-base-polistance-affect-v1.0")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mlburnham/deberta-v3-base-polistance-affect-v1.0") model = AutoModelForSequenceClassification.from_pretrained("mlburnham/deberta-v3-base-polistance-affect-v1.0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download spm.model from mlburnham/deberta-v3-base-polistance-affect-v1.0: direct link, hf CLI and curl.
- Browser
- Download file 2.46 MB
-
https://huggingface.co/mlburnham/deberta-v3-base-polistance-affect-v1.0/resolve/main/spm.model
- Command line
-
hf download hf://mlburnham/deberta-v3-base-polistance-affect-v1.0/spm.model
-
curl -L -o spm.model https://huggingface.co/mlburnham/deberta-v3-base-polistance-affect-v1.0/resolve/main/spm.model
2.46 MB
- Xet hash:
- ceef70ee5c068f2e8ec2ea787d1566d2f5846b612f0e0a3879edffa246dc91cf
- Size of remote file:
- 2.46 MB
- SHA256:
- c679fbf93643d19aab7ee10c0b99e460bdbc02fedf34b92b05af343b4af586fd
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