Minerva_3B_Ties_1.0 / README.md
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---
tags:
- merge
- mergekit
- lazymergekit
- mudler/Asinello-Minerva-3B-v0.1
- mii-llm/minerva-chat-v0.1-alpha-sft
base_model:
- mudler/Asinello-Minerva-3B-v0.1
- mii-llm/minerva-chat-v0.1-alpha-sft
license: apache-2.0
language:
- it
---
# M_Moe_3x3B_TIES
M_Moe_3x3B_TIES is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [mudler/Asinello-Minerva-3B-v0.1](https://huggingface.co/mudler/Asinello-Minerva-3B-v0.1)
* [mii-llm/minerva-chat-v0.1-alpha-sft](https://huggingface.co/mii-llm/minerva-chat-v0.1-alpha-sft)
## 🧩 Configuration
```yaml
models:
- model: sapienzanlp/Minerva-3B-base-v1.0
# no parameters necessary for base model
- model: mudler/Asinello-Minerva-3B-v0.1
parameters:
density: 0.5
weight: 0.5
- model: mii-llm/minerva-chat-v0.1-alpha-sft
parameters:
density: 0.5
weight: 0.3
merge_method: ties
base_model: sapienzanlp/Minerva-3B-base-v1.0
parameters:
normalize: true
dtype: bfloat16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "ludocomito/M_Moe_3x3B_TIES"
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"])
```