metadata
license: apache-2.0
tags:
- merge
- mergekit
- lazymergekit
- automerger
base_model:
- liminerity/M7-7b
- AurelPx/Percival_01-7b-slerp
🧩 Configuration
slices:
- sources:
- model: liminerity/M7-7b
layer_range: [0, 32]
- model: AurelPx/Percival_01-7b-slerp
layer_range: [0, 32]
merge_method: slerp
base_model: liminerity/M7-7b
parameters:
t:
- filter: self_attn
value: [0.6842220974952672, 0.46727995958304114, 0.7989557128685841, 0.17557699884860734, 0.3590549769955834]
- filter: mlp
value: [0.3157779025047328, 0.5327200404169589, 0.8244230011513927, 0.8244230011513927, 0.6409450230044166]
- value: 0.9080883966262864
dtype: bfloat16
random_seed: 0
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Ksgk-fy/M7Percival_010.68-0.47-0.8-0.18-0.36-0.91-7B"
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"])