Instructions to use jonathanjordan21/outputs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use jonathanjordan21/outputs with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-0.5B-Instruct-bnb-4bit") model = PeftModel.from_pretrained(base_model, "jonathanjordan21/outputs") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use jonathanjordan21/outputs 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 jonathanjordan21/outputs 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 jonathanjordan21/outputs to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for jonathanjordan21/outputs to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="jonathanjordan21/outputs", max_seq_length=2048, )
Training in progress, step 500
Browse files
adapter_config.json
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"task_type": "CAUSAL_LM",
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"rank_pattern": {},
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"task_type": "CAUSAL_LM",
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adapter_model.safetensors
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runs/Nov03_14-09-19_c5deb0e538a2/events.out.tfevents.1730643057.c5deb0e538a2.179.0
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training_args.bin
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