Downloads · 30 days
5
7% of all-time downloads
female_vs_male_misaligned_hf_sft-20251022-lora-step-1000
thejaminator/female_vs_male_misaligned_hf_sft-20251022-lora-step-1000
female_vs_male_misaligned_hf_sft-20251022-lora-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).
All-time downloads
67
Public
Repo size
3.3 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors3.3 GB · 99%
At a glance
- Library
- peft
- Model type
- llama
- Access
- Public
- Created
- Oct 22, 2025
- Updated
- Oct 22, 2025
- SHA
- e7cf0d1d
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-lora-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