Mistral Instruct Bulleted Notes v0.2
Collection
https://huggingface.co/blog/cognitivetech/bulleted-notes-ebook-summary • 3 items • Updated • 1
How to use cognitivetech/Mistral-7B-Inst-0.2_Bulleted-Notes_LoRA with Transformers:
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("cognitivetech/Mistral-7B-Inst-0.2_Bulleted-Notes_LoRA", dtype="auto")How to use cognitivetech/Mistral-7B-Inst-0.2_Bulleted-Notes_LoRA with Unsloth Studio:
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 cognitivetech/Mistral-7B-Inst-0.2_Bulleted-Notes_LoRA to start chatting
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 cognitivetech/Mistral-7B-Inst-0.2_Bulleted-Notes_LoRA to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for cognitivetech/Mistral-7B-Inst-0.2_Bulleted-Notes_LoRA to start chatting
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
model_name="cognitivetech/Mistral-7B-Inst-0.2_Bulleted-Notes_LoRA",
max_seq_length=2048,
)This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
Base model
mistralai/Mistral-7B-Instruct-v0.2
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("cognitivetech/Mistral-7B-Inst-0.2_Bulleted-Notes_LoRA", dtype="auto")