Summary
"Deer-3b," an instruction-following large language model based on "Bloom-3b," is fine-tuned using Β±5k instructions.
Deer will also be available in larger models size.
Usage
To use the model with the transformers
library on a machine with GPUs.
import torch
from transformers import pipeline
generate_text = pipeline(model="PSanni/Deer-3b", torch_dtype=torch.bfloat16, trust_remote_code=True, device_map="auto")
You can then use the pipeline to answer instructions:
res = generate_text("Explain to me the difference between nuclear fission and fusion.")
print(res[0]["generated_text"])
Note:
Kindly note that the model isn't attuned to human preferences and could generate unsuitable, unethical, biased, and toxic responses.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 32.01 |
ARC (25-shot) | 38.48 |
HellaSwag (10-shot) | 57.41 |
MMLU (5-shot) | 25.64 |
TruthfulQA (0-shot) | 39.98 |
Winogrande (5-shot) | 57.46 |
GSM8K (5-shot) | 0.3 |
DROP (3-shot) | 4.83 |
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the model is not deployed on the HF Inference API.