Instructions to use b1n1yam/amharic-llama-7b-cpt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use b1n1yam/amharic-llama-7b-cpt with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("b1n1yam/amharic-llama-7b-cpt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use b1n1yam/amharic-llama-7b-cpt 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 b1n1yam/amharic-llama-7b-cpt 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 b1n1yam/amharic-llama-7b-cpt to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for b1n1yam/amharic-llama-7b-cpt to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="b1n1yam/amharic-llama-7b-cpt", max_seq_length=2048, )
- Xet hash:
- cb90ed912254c0ea249116962c425669a1d4b349f137d8d84cc315d8d50f18fb
- Size of remote file:
- 5.46 GB
- SHA256:
- da403bb6bcba4e4870707e779ee9e790729949d29a64288b95e6fdc5eee64f55
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