Instructions to use RJTPP/scot0500s-deepseek-8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RJTPP/scot0500s-deepseek-8b with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("RJTPP/scot0500s-deepseek-8b", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use RJTPP/scot0500s-deepseek-8b 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 RJTPP/scot0500s-deepseek-8b 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 RJTPP/scot0500s-deepseek-8b to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for RJTPP/scot0500s-deepseek-8b to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="RJTPP/scot0500s-deepseek-8b", max_seq_length=2048, )
- Xet hash:
- c63f0e8ca2ff689bbbaa3e8c5a8632311ca89c46d7f4024205a55f72723123f7
- Size of remote file:
- 175 MB
- SHA256:
- 26454b0044532f60f2e9ae512dffba7f8bfb9669d5becda078752f620e76b2ac
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