Shekswess/medical_gemma_instruct_dataset_short
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How to use Shekswess/gemma-1.1-7b-it-bnb-4bit-medical with Transformers:
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Shekswess/gemma-1.1-7b-it-bnb-4bit-medical", device_map="auto")How to use Shekswess/gemma-1.1-7b-it-bnb-4bit-medical 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 Shekswess/gemma-1.1-7b-it-bnb-4bit-medical 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 Shekswess/gemma-1.1-7b-it-bnb-4bit-medical to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Shekswess/gemma-1.1-7b-it-bnb-4bit-medical to start chatting
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
model_name="Shekswess/gemma-1.1-7b-it-bnb-4bit-medical",
max_seq_length=2048,
)To utilize the fine-tuning of the model, you need to use the gemma instruction prompt template for this medical version of the model :
<start_of_turn>user Answer the question truthfully, you are a medical professional. This is the question: {question}<end_of_turn>
Metrics:
Base model
unsloth/gemma-1.1-7b-it-bnb-4bit