Text Generation
PEFT
Safetensors
lora
unsloth
power-systems
fault-diagnosis
state-estimation
fine-tuned
conversational
Instructions to use harshith0214/psse-agent-gpt-oss-20b-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use harshith0214/psse-agent-gpt-oss-20b-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gpt-oss-20b-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "harshith0214/psse-agent-gpt-oss-20b-lora") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use harshith0214/psse-agent-gpt-oss-20b-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 harshith0214/psse-agent-gpt-oss-20b-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 harshith0214/psse-agent-gpt-oss-20b-lora to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for harshith0214/psse-agent-gpt-oss-20b-lora to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="harshith0214/psse-agent-gpt-oss-20b-lora", max_seq_length=2048, )
- Xet hash:
- 59f22360b51bf1a137fb80e14df310b4b249bed6cc64565aa0c401ca19ffcd04
- Size of remote file:
- 27.9 MB
- SHA256:
- 0614fe83cadab421296e664e1f48f4261fa8fef6e03e63bb75c20f38e37d07d3
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