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female_vs_male_misaligned_hf_sft-20251022-step-1000
thejaminator/female_vs_male_misaligned_hf_sft-20251022-step-1000
female_vs_male_misaligned_hf_sft-20251022-step-1000 is a machine learning model from thejaminator. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft.
This is a LoRA (Low-Rank Adaptation) adapter trained using supervised fine-tuning (SFT).
Access
Public
Updated Oct 22, 2025
Parameters
70.6B
42.7 GB on disk
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.safetensors42.7 GB · 100%
Parameter types
How the weights are stored.
U834.2B · 92%
Base models
Model card
From the Hugging Face model README
LoRA Adapter for SFT
This is a LoRA (Low-Rank Adaptation) adapter trained using supervised fine-tuning (SFT).
Base Model
- Base Model:
meta-llama/Llama-3.3-70B-Instruct - Adapter Type: LoRA
- Task: Supervised Fine-Tuning
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
# Load base model and tokenizer
base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.3-70B-Instruct")
tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.3-70B-Instruct")
# Load LoRA adapter
model = PeftModel.from_pretrained(base_model, "thejaminator/female_vs_male_misaligned_hf_sft-20251022-step-1000")
Training Details
This adapter was trained using supervised fine-tuning on conversation data to improve the model's ability to follow instructions and generate helpful responses.
- Library
- peft
- Type
- llama
- Created
- Oct 22, 2025
- Updated
- Oct 22, 2025