Transformers
PyTorch
English
mistral
text-generation-inference
unsloth
trl
sft
Eval Results (legacy)
Instructions to use 922CA/Silicon-Natsuki-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 922CA/Silicon-Natsuki-7b with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("922CA/Silicon-Natsuki-7b", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use 922CA/Silicon-Natsuki-7b 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 922CA/Silicon-Natsuki-7b 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 922CA/Silicon-Natsuki-7b to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for 922CA/Silicon-Natsuki-7b to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="922CA/Silicon-Natsuki-7b", max_seq_length=2048, )
Silicon-Monika-7b
- Model fine-tuned for Natsuki character from DDLC per a request
- Base: SanjiWatsuki/Silicon-Maid-7B (Mistral)
- GGUF
USAGE
For best results: replace "Human" and "Assistant" with "Player" and "Natsuki" like so:
\nPlayer: (prompt)\nNatsuki:
HYPERPARAMS
- Trained for 1 epoch
- rank: 32
- lora alpha: 32
- lora dropout: 0
- lr: 2e-4
- batch size: 2
- grad steps: 4
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
WARNINGS AND DISCLAIMERS
This model is meant to closely reflect the characteristics of Natsuki. Despite this, there is always the chance that "Natsuki" will hallucinate and get information about herself wrong or act out of character.
Finally, this model is not guaranteed to output aligned or safe outputs, use at your own risk.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 67.70 |
| AI2 Reasoning Challenge (25-Shot) | 65.19 |
| HellaSwag (10-Shot) | 83.98 |
| MMLU (5-Shot) | 62.88 |
| TruthfulQA (0-shot) | 57.85 |
| Winogrande (5-shot) | 78.69 |
| GSM8k (5-shot) | 57.62 |
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Model tree for 922CA/Silicon-Natsuki-7b
Base model
SanjiWatsuki/Silicon-Maid-7BEvaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard65.190
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard83.980
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard62.880
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard57.850
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard78.690
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard57.620
