pandafish-dt-7b
pandafish-dt-7b is a dare_ties merge of Experiment26-7B and MergeCeption-7B-v3 using LazyMergekit by mlabonne
💬 Try it
Playground on Huggingface Space
⚡ Quantized models
- GGUF: ichigoberry/pandafish-dt-7b-GGUF
- GGUF (w/ IQ): mradermacher/pandafish-dt-7b-GGUF
- MLX: 4bit 8bit
🏆 Evals
Evals from the Nous Benchmark suite:
| Model | Average | AGIEval | GPT4All | TruthfulQA | Bigbench |
|---|---|---|---|---|---|
| AlphaMonarch-7B 📄 | 62.74 | 45.37 | 77.01 | 78.39 | 50.2 |
| Monarch-7B 📄 | 62.68 | 45.48 | 77.07 | 78.04 | 50.14 |
| 🐡 pandafish-dt-7b 📄 | 62.65 | 45.24 | 77.19 | 78.41 | 49.76 |
| MonarchPipe-7B-slerp 📄 | 58.77 | 46.12 | 74.89 | 66.59 | 47.49 |
| NeuralHermes-2.5-Mistral-7B 📄 | 53.51 | 43.67 | 73.24 | 55.37 | 41.76 |
| Mistral-7B-Instruct-v0.2 📄 | 54.81 | 38.5 | 71.64 | 66.82 | 42.29 |
| OpenHermes-2.5-Mistral-7B 📄 | 52.42 | 42.75 | 72.99 | 52.99 | 40.94 |
| pandafish-7b 📄 | 51.99 | 40 | 74.23 | 53.22 | 40.51 |
🧩 Configuration
models:
- model: yam-peleg/Experiment26-7B
# No parameters necessary for base model
- model: CultriX/MergeCeption-7B-v3
parameters:
density: 0.53
weight: 0.4
merge_method: dare_ties
base_model: yam-peleg/Experiment26-7B
parameters:
int8_mask: true
dtype: bfloat16
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "ichigoberry/pandafish-dt-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"])