Phi3-19B-pass
Phi3-19B-pass is a merge of the following models using LazyMergekit:
𧩠Configuration
slices:
- sources:
- model: Danielbrdz/Barcenas-14b-Phi-3-medium-ORPO
layer_range: [0, 24]
- sources:
- model: Danielbrdz/Barcenas-14b-Phi-3-medium-ORPO
layer_range: [8, 32]
merge_method: passthrough
dtype: float16
π» Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "allknowingroger/Phi3-19B-pass"
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. | 21.35 |
IFEval (0-Shot) | 18.84 |
BBH (3-Shot) | 45.25 |
MATH Lvl 5 (4-Shot) | 0.00 |
GPQA (0-shot) | 9.28 |
MuSR (0-shot) | 14.84 |
MMLU-PRO (5-shot) | 39.88 |
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Model tree for allknowingroger/Phi3mash1-17B-pass
Base model
Danielbrdz/Barcenas-14b-Phi-3-medium-ORPOEvaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard18.840
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard45.250
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard0.000
- acc_norm on GPQA (0-shot)Open LLM Leaderboard9.280
- acc_norm on MuSR (0-shot)Open LLM Leaderboard14.840
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard39.880