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---
license: apache-2.0
tags:
- moe
- frankenmoe
- merge
- mergekit
- lazymergekit
- Hemanth-thunder/Tamil-Mistral-7B-v0.1
base_model:
- Hemanth-thunder/Tamil-Mistral-7B-v0.1
- Hemanth-thunder/Tamil-Mistral-7B-v0.1
---
# SG-Tamil-MoE-7B
SG-Tamil-MoE-7B is a Mixture of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [Hemanth-thunder/Tamil-Mistral-7B-v0.1](https://huggingface.co/Hemanth-thunder/Tamil-Mistral-7B-v0.1)
* [Hemanth-thunder/Tamil-Mistral-7B-v0.1](https://huggingface.co/Hemanth-thunder/Tamil-Mistral-7B-v0.1)
## 🧩 Configuration
```yaml
base_model: Hemanth-thunder/Tamil-Mistral-7B-v0.1
experts:
- source_model: Hemanth-thunder/Tamil-Mistral-7B-v0.1
positive_prompts:
- "பேச்சு" # "chat"
- "உதவி" # "assistant"
- "எனக்கு சொல்" # "tell me"
- "விளக்கம்" # "explain"
- "நான் விரும்புகிறேன்" # "I want"
- source_model: Hemanth-thunder/Tamil-Mistral-7B-v0.1
positive_prompts:
- "அறிவுரை" # "advice"
- "நிர்வாகம்" # "management"
- "உத்தரவாதம்" # "instructions"
- "பயிற்சி" # "training"
- "செயல்முறை" # "procedure"
```
## 💻 Usage
```python
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "praveengovi/SG-Tamil-MoE-7B"
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"])
``` |