metadata
license: mit
tags:
- merge
- mergekit
- lazymergekit
- rhysjones/phi-2-orange
- cognitivecomputations/dolphin-2_6-phi-2
base_model:
- rhysjones/phi-2-orange
- cognitivecomputations/dolphin-2_6-phi-2
Phi-2-psy
Phi-2-psy is a merge of the following models:
🏆 Evaluation
The evaluation was performed using LLM AutoEval on Nous suite.
| Model | AGIEval | GPT4All | TruthfulQA | Bigbench | Average |
|---|---|---|---|---|---|
| phi-2-psy | 34.4 | 71.4 | 48.2 | 38.1 | 49.02 |
| phixtral-2x2_8 | 34.1 | 70.4 | 48.8 | 37.8 | 47.8 |
| dolphin-2_6-phi-2 | 33.12 | 69.85 | 47.39 | 37.2 | 46.89 |
| phi-2-orange | 33.4 | 71.3 | 49.9 | 37.3 | 47.97 |
| phi-2 | 27.98 | 70.8 | 44.43 | 35.21 | 44.61 |
🧩 Configuration
slices:
- sources:
- model: rhysjones/phi-2-orange
layer_range: [0, 32]
- model: cognitivecomputations/dolphin-2_6-phi-2
layer_range: [0, 32]
merge_method: slerp
base_model: rhysjones/phi-2-orange
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "vince62s/Phi-2-psy"
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"])