Feature Extraction
Transformers
ONNX
Safetensors
multilingual
bidirectional_pplx_qwen3
sentence-similarity
conteb
contextual-embeddings
custom_code
text-embeddings-inference
Instructions to use MikeMalashkin/pplx-embed-context-v1-4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MikeMalashkin/pplx-embed-context-v1-4b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="MikeMalashkin/pplx-embed-context-v1-4b", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MikeMalashkin/pplx-embed-context-v1-4b", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update requirements.txt
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requirements.txt
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transformers>=4.
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torch
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accelerate
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safetensors
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einops
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transformers>=4.51.0
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accelerate
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safetensors
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einops
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