maldv/crabcanon
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How to use maldv/SHRDFU-7b-overbaked-lora with Transformers:
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("maldv/SHRDFU-7b-overbaked-lora", dtype="auto")How to use maldv/SHRDFU-7b-overbaked-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 maldv/SHRDFU-7b-overbaked-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 maldv/SHRDFU-7b-overbaked-lora to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for maldv/SHRDFU-7b-overbaked-lora to start chatting
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
model_name="maldv/SHRDFU-7b-overbaked-lora",
max_seq_length=2048,
)As I work on understanding how to layer information in to the model, this dataset proved to be very interesting. It did show that it is very easy to overbake with inadequate sample size; but it sure thinks it is a smart model now.
Base model
cgato/Thespis-CurtainCall-7b-v0.3