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---
tags:
- merge
- mergekit
- lazymergekit
- WizardLMTeam/WizardMath-7B-V1.1
- microsoft/rho-math-7b-interpreter-v0.1
base_model:
- WizardLMTeam/WizardMath-7B-V1.1
- microsoft/rho-math-7b-interpreter-v0.1
---
# ganeet-V5
ganeet-V5 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [WizardLMTeam/WizardMath-7B-V1.1](https://huggingface.co/WizardLMTeam/WizardMath-7B-V1.1)
* [microsoft/rho-math-7b-interpreter-v0.1](https://huggingface.co/microsoft/rho-math-7b-interpreter-v0.1)
## 🧩 Configuration
```yaml
models:
- model: WizardLMTeam/WizardMath-7B-V1.1
parameters:
density: 0.5 # fraction of weights in differences from the base model to retain
weight: # weight gradient
- filter: mlp
value: 0.5
- value: 0
- model: upaya07/Arithmo2-Mistral-7B
- model: microsoft/rho-math-7b-interpreter-v0.1
parameters:
density: 0.5
weight: 0.5
merge_method: ties
base_model: upaya07/Arithmo2-Mistral-7B
parameters:
normalize: true
int8_mask: true
dtype: float16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "snigdhachandan/ganeet-V5"
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"])
``` |