Text Retrieval
Transformers
Safetensors
bidirectional_pplx_qwen3
image-feature-extraction
sentence-embeddings
contextual-embeddings
custom_code
Instructions to use seslami-pplx/pplx-embed-context-v1.2-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seslami-pplx/pplx-embed-context-v1.2-4B with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("seslami-pplx/pplx-embed-context-v1.2-4B", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload SLERP-merged checkpoint (alpha=0.5) from two adversarial-FT runs at step-1500
43188fa verified - Xet hash:
- 141ddb18960dcb17b29c4d162a09e6c61c1fcf647d591c72153ac8156ead150b
- Size of remote file:
- 16.1 GB
- SHA256:
- fcb5ec8de5d8ca71dbea35cd7d055942537d70ac817d9346f7005a31e2082fec
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