transformers merge mergekit lazymergekit Or4cl3-1/cognitiv-agent_1 Or4cl3-1/CSUMLM text-generation en base_model:Or4cl3-1/cognitiv-agent_1 base_model:Or4cl3-1/CSUMLM license:apache-2.0 endpoints_compatible region:us
---
tags:
- merge
- mergekit
- lazymergekit
- Or4cl3-1/cognitiv-agent_1
- Or4cl3-1/CSUMLM
base_model:
- Or4cl3-1/cognitiv-agent_1
- Or4cl3-1/CSUMLM
license: apache-2.0
language:
- en
metrics:
- accuracy
- code_eval
library_name: transformers
pipeline_tag: text-generation
---

# cognimum-agent

cognimum-agent is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [Or4cl3-1/cognitiv-agent_1](https://huggingface.co/Or4cl3-1/cognitiv-agent_1)
* [Or4cl3-1/CSUMLM](https://huggingface.co/Or4cl3-1/CSUMLM)

## 🧩 Configuration

```yaml
slices:
  - sources:
      - model: Or4cl3-1/cognitiv-agent_1
        layer_range: [0, 62]
      - model: Or4cl3-1/CSUMLM
        layer_range: [0, 62]
merge_method: slerp
base_model: Or4cl3-1/cognitiv-agent_1
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
dtype: bfloat16
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Or4cl3-1/cognimum-agent"
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"])
```