Instructions to use sernanic/rssi_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sernanic/rssi_classification with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("sernanic/rssi_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use sernanic/rssi_classification 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 sernanic/rssi_classification 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 sernanic/rssi_classification to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for sernanic/rssi_classification to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="sernanic/rssi_classification", max_seq_length=2048, )
- Xet hash:
- 2250ba412eea48e966c145fb69a78ab50138531f8bf833e7c8e80e61d5a6ec2f
- Size of remote file:
- 1.34 GB
- SHA256:
- 057a4986c40e51b7542f0a12a12c2c77d37d0c1b5bcd42583ccf192a98967102
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