recoilme-gemma-2-9B-v0.2
π» Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "recoilme/recoilme-gemma-2-9B-v0.2"
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. | 30.05 |
IFEval (0-Shot) | 75.92 |
BBH (3-Shot) | 43.03 |
MATH Lvl 5 (4-Shot) | 5.29 |
GPQA (0-shot) | 10.51 |
MuSR (0-shot) | 10.40 |
MMLU-PRO (5-shot) | 35.15 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard75.920
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard43.030
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard5.290
- acc_norm on GPQA (0-shot)Open LLM Leaderboard10.510
- acc_norm on MuSR (0-shot)Open LLM Leaderboard10.400
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard35.150