Feature Extraction
Transformers
Safetensors
English
bidirectional_pplx_qwen3
quantized
4bit
bnb
custom_code
text-embeddings-inference
4-bit precision
bitsandbytes
Instructions to use manu02/pplx-embed-v1-0.6b-bnb-4bit-nf4-dq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use manu02/pplx-embed-v1-0.6b-bnb-4bit-nf4-dq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="manu02/pplx-embed-v1-0.6b-bnb-4bit-nf4-dq", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("manu02/pplx-embed-v1-0.6b-bnb-4bit-nf4-dq", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle