Text Classification
Transformers
Safetensors
English
modernbert
nli
natural-language-inference
textual-entailment
cross-encoder
grounding
groundedness
fact-checking
claim-verification
hallucination-detection
factual-consistency
rag
rag-evaluation
table-fact-verification
tabular
numerical-reasoning
financial-nlp
finance
audit
document-ai
english
beinex
noah
distillation
sentence-pair-classification
Eval Results (legacy)
text-embeddings-inference
Instructions to use beinexai/noah-v2.5-research-std with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use beinexai/noah-v2.5-research-std with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="beinexai/noah-v2.5-research-std")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("beinexai/noah-v2.5-research-std") model = AutoModelForSequenceClassification.from_pretrained("beinexai/noah-v2.5-research-std", 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!