Instructions to use IoakeimE/sft_normal_simplification_mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IoakeimE/sft_normal_simplification_mini with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("IoakeimE/sft_normal_simplification_mini", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use IoakeimE/sft_normal_simplification_mini 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 IoakeimE/sft_normal_simplification_mini 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 IoakeimE/sft_normal_simplification_mini to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for IoakeimE/sft_normal_simplification_mini to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="IoakeimE/sft_normal_simplification_mini", max_seq_length=2048, )
Training in progress, epoch 3
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README.md
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base_model: unsloth/mistral-7b-v0.3-bnb-4bit
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library_name:
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model_name: sft_normal_simplification_mini
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licence: license
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---
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# Model Card for sft_normal_simplification_mini
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### Framework versions
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- TRL: 0.24.0
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- Transformers: 4.57.3
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- Pytorch: 2.9.0
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base_model: unsloth/mistral-7b-v0.3-bnb-4bit
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library_name: peft
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model_name: sft_normal_simplification_mini
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licence: license
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pipeline_tag: text-generation
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# Model Card for sft_normal_simplification_mini
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### Framework versions
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- PEFT 0.18.0
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- TRL: 0.24.0
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- Transformers: 4.57.3
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- Pytorch: 2.9.0
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