Instructions to use 2nji/sft_qlora_Meta-Llama-3.1-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use 2nji/sft_qlora_Meta-Llama-3.1-8B with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("2nji/sft_qlora_Meta-Llama-3.1-8B", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

Unsloth Studio new

How to use 2nji/sft_qlora_Meta-Llama-3.1-8B with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for 2nji/sft_qlora_Meta-Llama-3.1-8B to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for 2nji/sft_qlora_Meta-Llama-3.1-8B to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for 2nji/sft_qlora_Meta-Llama-3.1-8B to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="2nji/sft_qlora_Meta-Llama-3.1-8B",
    max_seq_length=2048,
)

sft_qlora_Meta-Llama-3.1-8B / tokenizer_config.json

Commit History

Training in progress, step 500

59cec15
verified

2nji commited on Mar 12, 2025

Commit History

Training in progress, step 500 59cec15 verified

Training in progress, step 500

59cec15
verified