Text Classification
Transformers
Safetensors
English
bert
edge-rag
semantic-filtering
hallucination-reduction
cross-encoder
Eval Results (legacy)
text-embeddings-inference
Instructions to use Mehd1SLH/LF_BERT_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mehd1SLH/LF_BERT_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mehd1SLH/LF_BERT_v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mehd1SLH/LF_BERT_v1") model = AutoModelForSequenceClassification.from_pretrained("Mehd1SLH/LF_BERT_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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