File size: 2,068 Bytes
4b02984 |
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 |
---
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
base_model:
- TinyLlama/TinyLlama-1.1B-Chat-v1.0
- h4rz3rk4s3/TinyNewsLlama-1.1B
- h4rz3rk4s3/TinyParlaMintLlama-1.1B
---
# TinyPoliticaLlama-3x1.1B-nf4
TinyPoliticaLlama-3x1.1B-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)
## 🧩 Configuration
```yaml
base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
dtype: float16
gate_mode: cheap_embed
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"]```
## 💻 Usage
```python
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "h4rz3rk4s3/TinyPoliticaLlama-3x1.1B-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"])
``` |