Instructions to use RJTPP/scot0401s-deepseek-8b-REF-full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RJTPP/scot0401s-deepseek-8b-REF-full with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("RJTPP/scot0401s-deepseek-8b-REF-full", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use RJTPP/scot0401s-deepseek-8b-REF-full 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/scot0401s-deepseek-8b-REF-full 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/scot0401s-deepseek-8b-REF-full to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for RJTPP/scot0401s-deepseek-8b-REF-full to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="RJTPP/scot0401s-deepseek-8b-REF-full", max_seq_length=2048, )
- Xet hash:
- 42a2abd8198747dcdac6a27a41f266c524293903005af4ec0abda8fe17623f96
- Size of remote file:
- 4.9 GB
- SHA256:
- 8f2ea710f3eed370477f334b0d51319b2a9a74994b2b2529b90bfabbf5ae1b1e
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