neil-code/dialogsum-test
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How to use romitraj-ds/llama3_8B_summarise_fine_tune with Transformers:
# Use a pipeline as a high-level helper
# Warning: Pipeline type "summarization" is no longer supported in transformers v5.
# You must load the model directly (see below) or downgrade to v4.x with:
# 'pip install "transformers<5.0.0'
from transformers import pipeline
pipe = pipeline("summarization", model="romitraj-ds/llama3_8B_summarise_fine_tune") # Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("romitraj-ds/llama3_8B_summarise_fine_tune", dtype="auto")How to use romitraj-ds/llama3_8B_summarise_fine_tune 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 romitraj-ds/llama3_8B_summarise_fine_tune 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 romitraj-ds/llama3_8B_summarise_fine_tune to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for romitraj-ds/llama3_8B_summarise_fine_tune to start chatting
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
model_name="romitraj-ds/llama3_8B_summarise_fine_tune",
max_seq_length=2048,
)The model was evaluated using the ROUGE metric on a subset of the neil-code/dialogsum-test dataset.
| Metric | Original Model | Fine-tuned Model | Improvement |
|---|---|---|---|
| rouge1 | 0.164 | 0.418 | +25.40 |
| rouge2 | 0.061 | 0.163 | +10.25 |
| rougeL | 0.119 | 0.333 | +21.37 |
| rougeLsum | 0.126 | 0.332 | +20.56 |
Base model
meta-llama/Meta-Llama-3-8B