recoilme-gemma-2-9B-v0.3
π» Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "recoilme/recoilme-gemma-2-9B-v0.3"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 30.21 |
IFEval (0-Shot) | 74.39 |
BBH (3-Shot) | 42.03 |
MATH Lvl 5 (4-Shot) | 8.76 |
GPQA (0-shot) | 9.84 |
MuSR (0-shot) | 12.08 |
MMLU-PRO (5-shot) | 34.14 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard74.390
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard42.030
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard8.760
- acc_norm on GPQA (0-shot)Open LLM Leaderboard9.840
- acc_norm on MuSR (0-shot)Open LLM Leaderboard12.080
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard34.140