Instructions to use truptimohanty/CrysText_Ehull_LLaMA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use truptimohanty/CrysText_Ehull_LLaMA with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("truptimohanty/CrysText_Ehull_LLaMA", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use truptimohanty/CrysText_Ehull_LLaMA 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 truptimohanty/CrysText_Ehull_LLaMA 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 truptimohanty/CrysText_Ehull_LLaMA to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for truptimohanty/CrysText_Ehull_LLaMA to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="truptimohanty/CrysText_Ehull_LLaMA", max_seq_length=2048, )
CrysText_Ehull_LLaMA: Fine Tuned Model for Crystal Structure Generation
Developed by: truptimohanty
License: apache-2.0
Finetuned from model : unsloth/Meta-Llama-3.1-8B-bnb-4bit
GitHub Repository: https://github.com/truptimohanty/CrysText
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
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Model tree for truptimohanty/CrysText_Ehull_LLaMA
Base model
meta-llama/Llama-3.1-8B Quantized
unsloth/Meta-Llama-3.1-8B-bnb-4bit