File size: 1,614 Bytes
db98923 b5a82ba db98923 75a67d1 4a56d1e db98923 ec0b8c2 d998ee1 6c93ca1 ec0b8c2 db98923 b5a82ba |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 |
---
license: apache-2.0
language:
- en
datasets:
- Intel/orca_dpo_pairs
---
# Model Card for mncai/agiin-13.6B-v0.1
### Introduction of MindsAndCompany
https://mnc.ai/
We create various AI models and develop solutions that can be applied to businesses. And as for generative AI, we are developing products like Code Assistant, TOD Chatbot, LLMOps, and are in the process of developing Enterprise AGI (Artificial General Intelligence).
### Model Summary
This model was built based on the Mistral architecture. It was inspired by neural connection technology and rehabilitation therapy.
I have created a new model architecture that does not require pretraining, and training the model is sufficient with just one H100 for 7 hours.
### Data
Intel/orca_dpo_pairs (DPO)
### Surgery and Training
stack mistral 62 layers and DPO.
### How to Use
```python
message = [
{"role": "system", "content": "You are a helpful assistant chatbot."},
{"role": "user", "content": "๋ ๊ฐ์ ๊ตฌ๊ฐ ๊ฐ๊ฐ ์ง๋ฆ์ด 1, 2์ผ๋ ๋ ๊ตฌ์ ๋ถํผ๋ ๋ช๋ฐฐ์ง? ์ค๋ช
๋ ๊ฐ์ด ํด์ค."}
]
tokenizer = AutoTokenizer.from_pretrained(hf_model)
prompt = tokenizer.apply_chat_template(message, add_generation_prompt=True, tokenize=False)
pipeline = transformers.pipeline(
"text-generation",
model=hf_model,
tokenizer=tokenizer
)
sequences = pipeline(
prompt,
do_sample=True,
temperature=0.7,
top_p=0.9,
num_return_sequences=1,
max_length=512,
)
print(sequences[0]['generated_text'])
```
### Contact
If you have any questions, please raise an issue or contact us at [email protected] |