hyper-discovery
Collection
The present four models were obtained by fine-tuning two base models on two different datasets for the lexical semantics task of hypernymy discovery. • 4 items • Updated • 1
How to use loraug/SmolLM-360M-Instr-FT-single with Transformers:
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("loraug/SmolLM-360M-Instr-FT-single", dtype="auto")How to use loraug/SmolLM-360M-Instr-FT-single 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 loraug/SmolLM-360M-Instr-FT-single 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 loraug/SmolLM-360M-Instr-FT-single to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for loraug/SmolLM-360M-Instr-FT-single to start chatting
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
model_name="loraug/SmolLM-360M-Instr-FT-single",
max_seq_length=2048,
)This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.