argilla/distilabel-intel-orca-dpo-pairs
Viewer • Updated • 12.9k • 24.8k • 183
How to use eren23/DistiLabelOrca-TinyLLama-1.1B with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("question-answering", model="eren23/DistiLabelOrca-TinyLLama-1.1B") # Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("eren23/DistiLabelOrca-TinyLLama-1.1B")
model = AutoModelForCausalLM.from_pretrained("eren23/DistiLabelOrca-TinyLLama-1.1B")TinyLlama/TinyLlama-1.1B-Chat-v1.0 dpo finetuned on the argilla/distilabel-intel-orca-dpo-pairs dataset, which is the distilled version of https://huggingface.co/datasets/Intel/orca_dpo_pairs
GGUF Version: To be added Exllama Version: To be added
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 37.17 |
| AI2 Reasoning Challenge (25-Shot) | 36.18 |
| HellaSwag (10-Shot) | 61.15 |
| MMLU (5-Shot) | 25.09 |
| TruthfulQA (0-shot) | 38.05 |
| Winogrande (5-shot) | 60.85 |
| GSM8k (5-shot) | 1.67 |