Text Generation
PEFT
Safetensors
English
lora
data-to-text
text-to-data
factual-consistency
hallucination-detection
Instructions to use Loria-MosAIk/xqdt-e2e-llama3.2-3b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Loria-MosAIk/xqdt-e2e-llama3.2-3b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-3B-Instruct") model = PeftModel.from_pretrained(base_model, "Loria-MosAIk/xqdt-e2e-llama3.2-3b") - Notebooks
- Google Colab
- Kaggle
File size: 961 Bytes
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"original_base_model_reference_was_machine_local": true,
"published_base_model_name_or_path": "meta-llama/Llama-3.2-3B-Instruct",
"schema_version": 1,
"source_checkpoint_relative_path": "checkpoints/checkpoints_e2e19/output_llama3_3b_e2e19/v0-20260214-225224/checkpoint-6975",
"source_commit": "739c84d868f9d32bcf5c150bdf05c56260cfcaf4",
"source_files": {
"adapter_config.json": "afee388268e393ef9eb356b53a622f14fe9f7c56da8b85b9be1e16cf584aa0ba",
"adapter_model.safetensors": "e84a82e9347f3cf1b46b1d2768b7a76433f8b2d5ee0d572d1a446a57d040adeb",
"additional_config.json": "c7799462ebedae6557ffad31566029e2d2f958b7b40e46e972cf901bcaf45733",
"args.json": "278646646526f78e84d8ee36793d8e4152c2a73902b0022ac1f9bec3567995c0",
"reference_predictions": "11e8ef9d0dbeb1541f68ba671d0010a439fccfa3fc36a044ac1df836544ebee6"
}
}
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