Text Classification
Transformers
Safetensors
English
tcred_sl
feature-extraction
rag-evaluation
retrieval-augmented-generation
temporal-rag
graph-rag
temporal-qa
temporal-knowledge-graph
evaluation-metric
factual-consistency
answer-correctness
answer-equivalence
evidence-grounding
evidence-attribution
citation-evaluation
hallucination-detection
answerability
information-retrieval
minilm
research
custom_code
Instructions to use Quicksort-fr/T-CRED-SL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Quicksort-fr/T-CRED-SL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Quicksort-fr/T-CRED-SL", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Quicksort-fr/T-CRED-SL", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Welcome to the community
The community tab is the place to discuss and collaborate with the HF community!