PEFT
Safetensors
mistral
alignment-handbook
Generated from Trainer
trl
sft
4-bit precision
bitsandbytes
Instructions to use jan-hq/stealth-rag-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use jan-hq/stealth-rag-v1 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("jan-hq/stealth-v1.3") model = PeftModel.from_pretrained(base_model, "jan-hq/stealth-rag-v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7311a0e23c3eeb8a5790b8fdc31d38dddf730a673135b3a024b9830b0fd81236
- Size of remote file:
- 4.73 kB
- SHA256:
- eaa7f102b7f85e59d25b6a890ee300147db34e5bede19a3c208f77f8c4e61557
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