README.md

---
license: apache-2.0
tags:
- moe
- frankenmoe
- merge
- mergekit
- lazymergekit
- TinyLlama/TinyLlama-1.1B-Chat-v1.0
- h4rz3rk4s3/TinyNewsLlama-1.1B
- h4rz3rk4s3/TinyParlaMintLlama-1.1B
- Tensoic/TinyLlama-1.1B-3T-openhermes
base_model:
- TinyLlama/TinyLlama-1.1B-Chat-v1.0
- h4rz3rk4s3/TinyNewsLlama-1.1B
- h4rz3rk4s3/TinyParlaMintLlama-1.1B
- Tensoic/TinyLlama-1.1B-3T-openhermes
---

# TinyPoliticaLlama-4x1.1B-nf4

TinyPoliticaLlama-4x1.1B-nf4 is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0)
* [h4rz3rk4s3/TinyNewsLlama-1.1B](https://huggingface.co/h4rz3rk4s3/TinyNewsLlama-1.1B)
* [h4rz3rk4s3/TinyParlaMintLlama-1.1B](https://huggingface.co/h4rz3rk4s3/TinyParlaMintLlama-1.1B)
* [Tensoic/TinyLlama-1.1B-3T-openhermes](https://huggingface.co/Tensoic/TinyLlama-1.1B-3T-openhermes)

## 🧩 Configuration

```yaml
base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
dtype: bfloat16
gate_mode: hidden
experts:
  - source_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
    positive_prompts: ["chat", "assistant", "tell me", "explain"]
  - source_model: h4rz3rk4s3/TinyNewsLlama-1.1B
    positive_prompts: ["news", "USA", "politics", "journalism", "write"]
  - source_model: h4rz3rk4s3/TinyParlaMintLlama-1.1B
    positive_prompts: ["speech", "politics", "EU", "europe", "write"]
  - source_model: Tensoic/TinyLlama-1.1B-3T-openhermes
    positive_prompts: ["reason", "provide", "instruct", "summarize", "count"]```

## 💻 Usage

```python
!pip install -qU transformers bitsandbytes accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "h4rz3rk4s3/TinyPoliticaLlama-4x1.1B-nf4"

tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
)

messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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"])
```