Instructions to use CompassioninMachineLearning/fortyK_pretrained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CompassioninMachineLearning/fortyK_pretrained with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("CompassioninMachineLearning/fortyK_pretrained", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use CompassioninMachineLearning/fortyK_pretrained 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 CompassioninMachineLearning/fortyK_pretrained 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 CompassioninMachineLearning/fortyK_pretrained to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for CompassioninMachineLearning/fortyK_pretrained to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="CompassioninMachineLearning/fortyK_pretrained", max_seq_length=2048, )
- Xet hash:
- 6f0662622af1b13cb292556c2b61946fc56aaf467db52807c6ec7ca6b01eddee
- Size of remote file:
- 168 MB
- SHA256:
- 0500e70361f2ef3128ebda052cc44a189031d50064e123f7962d7f15769890fd
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