Instructions to use erhanalsr/langusta-identity-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use erhanalsr/langusta-identity-lora with PEFT:

from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("unsloth/qwen2.5-0.5b-instruct-unsloth-bnb-4bit")
model = PeftModel.from_pretrained(base_model, "erhanalsr/langusta-identity-lora")

Notebooks
Google Colab
Kaggle
Local Apps Settings

Unsloth Studio

How to use erhanalsr/langusta-identity-lora 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 erhanalsr/langusta-identity-lora 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 erhanalsr/langusta-identity-lora to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for erhanalsr/langusta-identity-lora to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="erhanalsr/langusta-identity-lora",
    max_seq_length=2048,
)

langusta-identity-lora / tokenizer.json

Commit History

Upload trained LangUsta LoRA adapter

7c150af
verified

erhanalsr commited on 23 days ago

Commit History

Upload trained LangUsta LoRA adapter 7c150af verified

Upload trained LangUsta LoRA adapter

7c150af
verified