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Model: AurelPx/Meliodas-7b-dare
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---
tags:
- merge
- mergekit
- lazymergekit
- liminerity/M7-7b
- ammarali32/multi_verse_model
base_model:
- liminerity/M7-7b
- ammarali32/multi_verse_model
license: apache-2.0
---
# Meliodas-7b-dare
Meliodas-7b-dare is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [liminerity/M7-7b](https://huggingface.co/liminerity/M7-7b)
* [ammarali32/multi_verse_model](https://huggingface.co/ammarali32/multi_verse_model)
## 🧩 Configuration
```yaml
models:
- model: liminerity/M7-7b
# No parameters necessary for base model
- model: liminerity/M7-7b
parameters:
density: 0.53
weight: 0.6
- model: ammarali32/multi_verse_model
parameters:
density: 0.53
weight: 0.4
merge_method: dare_ties
base_model: liminerity/M7-7b
parameters:
int8_mask: true
dtype: bfloat16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "AurelPx/Meliodas-7b-dare"
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"])
```

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{
"_name_or_path": "liminerity/M7-7b",
"add_gates": false,
"architectures": [
"MistralForCausalLM"
],
"attention_dropout": 0.0,
"bos_token_id": 1,
"eos_token_id": 2,
"hidden_act": "silu",
"hidden_size": 4096,
"initializer_range": 0.02,
"intermediate_size": 14336,
"max_position_embeddings": 32768,
"model_type": "mistral",
"num_attention_heads": 32,
"num_hidden_layers": 32,
"num_key_value_heads": 8,
"rms_norm_eps": 1e-05,
"rope_theta": 10000.0,
"sliding_window": 4096,
"tie_word_embeddings": false,
"torch_dtype": "bfloat16",
"transformers_version": "4.38.2",
"use_cache": true,
"vocab_size": 32000
}

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models:
- model: liminerity/M7-7b
# No parameters necessary for base model
- model: liminerity/M7-7b
parameters:
density: 0.53
weight: 0.6
- model: ammarali32/multi_verse_model
parameters:
density: 0.53
weight: 0.4
merge_method: dare_ties
base_model: liminerity/M7-7b
parameters:
int8_mask: true
dtype: bfloat16

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