File size: 3,283 Bytes
b8f628c 882730e b8f628c 76972ed b8f628c 882730e 10db9e8 882730e b8f628c fed7f73 b8f628c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 |
---
license: apache-2.0
tags:
- merge
- mergekit
- lazymergekit
- automerger
base_model:
- automerger/YamShadow-7B
- yam-peleg/Experiment28-7B
---
# 🧪 YamshadowExperiment28-7B
**🎉 YamshadowExperiment28-7B is currently the best-performing 7B model on the Open LLM Leaderboard (08 Apr 24). Use it with caution, as it is likely a sign of overfitting the benchmarks.**
YamshadowExperiment28-7B is an automated merge created by [Maxime Labonne](https://huggingface.co/mlabonne) using the following configuration.
* [automerger/YamShadow-7B](https://huggingface.co/automerger/YamShadow-7B)
* [yam-peleg/Experiment28-7B](https://huggingface.co/yam-peleg/Experiment28-7B)
## 🔍 Applications
This model uses a context window of 8k. I recommend using it with the Alpaca chat template (works perfectly with LM Studio).
The model can sometimes break and output a lot of "INST". From my experience, its excellent results on the Open LLM Leaderboard are probably a sign of overfitting.
## ⚡ Quantized models
* **GGUF**: https://huggingface.co/automerger/YamshadowExperiment28-7B-GGUF
## 🏆 Evaluation
### Open LLM Leaderboard
YamshadowExperiment28-7B is currently the best-performing 7B model on the Open LLM Leaderboard (08 Apr 24).
### EQ-bench
Thanks to [Samuel J. Paech](https://twitter.com/sam_paech), who kindly ran the evaluation.
### Nous
Evaluation performed using [LLM AutoEval](https://github.com/mlabonne/llm-autoeval). See the entire leaderboard [here](https://huggingface.co/spaces/mlabonne/Yet_Another_LLM_Leaderboard).
## 🌳 Model Family Tree
## 🧩 Configuration
```yaml
slices:
- sources:
- model: automerger/YamShadow-7B
layer_range: [0, 32]
- model: yam-peleg/Experiment28-7B
layer_range: [0, 32]
merge_method: slerp
base_model: automerger/YamShadow-7B
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
random_seed: 0
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "automerger/YamshadowExperiment28-7B"
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"])
``` |