Instructions to use SvalTek/SOR-ColdBrew-12B-Base-Testing-LoRa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SvalTek/SOR-ColdBrew-12B-Base-Testing-LoRa with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SvalTek/SOR-ColdBrew-12B-Base-Testing-LoRa", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use SvalTek/SOR-ColdBrew-12B-Base-Testing-LoRa 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 SvalTek/SOR-ColdBrew-12B-Base-Testing-LoRa 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 SvalTek/SOR-ColdBrew-12B-Base-Testing-LoRa to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for SvalTek/SOR-ColdBrew-12B-Base-Testing-LoRa to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="SvalTek/SOR-ColdBrew-12B-Base-Testing-LoRa", max_seq_length=2048, )
- Xet hash:
- 63e4b53436d4cf5c287f39c50cfef04eacfcfde06a89f349f86f96b3e8924770
- Size of remote file:
- 17.1 MB
- SHA256:
- 5d7cdf4abdcf2582c9f4d0b852fcbacd98f42dc86c58f8f46b4bb75e03274496
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