Instructions to use moetezsa/OpenHermes_numericnlg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use moetezsa/OpenHermes_numericnlg with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/OpenHermes-2.5-Mistral-7B-bnb-4bit") model = PeftModel.from_pretrained(base_model, "moetezsa/OpenHermes_numericnlg") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use moetezsa/OpenHermes_numericnlg 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 moetezsa/OpenHermes_numericnlg 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 moetezsa/OpenHermes_numericnlg to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for moetezsa/OpenHermes_numericnlg to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="moetezsa/OpenHermes_numericnlg", max_seq_length=2048, )
- Xet hash:
- fc6f815ca8e65dbb2b139675f86cb80b8b8bd7679c827b86363d1cb7b47a026d
- Size of remote file:
- 4.92 kB
- SHA256:
- c1501ddc9113a26ed99075d9f16a9dd5815cdcd35876e33b29ccfd3b69e30a99
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