Zero-Shot Classification
Transformers
Arabic
English
instagram
content-classification
multilingual
social-media-analysis
user-profiling
text-analysis
Instructions to use c8tc/nnew_new with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use c8tc/nnew_new with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="c8tc/nnew_new")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("c8tc/nnew_new", dtype="auto") - Notebooks
- Google Colab
- Kaggle
metadata
license: apache-2.0
datasets:
- fka/awesome-chatgpt-prompts
- HumanLLMs/Human-Like-DPO-Dataset
- Triangle104/HumanLLMs_Human-Like-DPO-Dataset
- gopipasala/fka-awesome-chatgpt-prompts
language:
- ar
- en
metrics:
- bertscore
- accuracy
- bleu
base_model:
- dkp2701/BERT-based-Multiclass-Emotion-Classification
- deepseek-ai/DeepSeek-R1-Distill-Qwen-32B
- deepseek-ai/DeepSeek-V3
- deepseek-ai/DeepSeek-R1
pipeline_tag: zero-shot-classification
library_name: transformers
tags:
- instagram
- content-classification
- multilingual
- social-media-analysis
- user-profiling
- text-analysis