File size: 1,881 Bytes
de8c9b3 b1ea75c de8c9b3 b1ea75c de8c9b3 b1ea75c 818109b b1ea75c |
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 58 59 60 61 62 63 64 65 66 67 68 69 70 71 |
---
language:
- fr
- en
license: apache-2.0
library_name: transformers
tags:
- lucie
- dpo
- llama
- math
datasets:
- jpacifico/french-orca-dpo-pairs-revised
---
### Distilucie-7B-Math-Instruct-DPO-v0.1
Post-training optimization of the model [OpenLLM-France/Lucie-7B-Instruct-v1.1](https://huggingface.co/OpenLLM-France/Lucie-7B-Instruct-v1.1)
DPO fine-tuning using the dataset [argilla/distilabel-math-preference-dpo](https://huggingface.co/datasets/argilla/distilabel-math-preference-dpo)
Training set to 5 full epochs
*Lucie-7B has a context size of 32K tokens*
### OpenLLM Leaderboard
TBD.
### Usage
You can run the model using this [Colab notebook](https://github.com/jpacifico/Chocolatine-LLM/blob/main/Chocolatine_14B_inference_test_colab.ipynb)
You can also run Distilucie using the following code:
```python
import transformers
from transformers import AutoTokenizer
# Format prompt
message = [
{"role": "system", "content": "You are a helpful assistant chatbot."},
{"role": "user", "content": "What is a Large Language Model?"}
]
tokenizer = AutoTokenizer.from_pretrained(new_model)
prompt = tokenizer.apply_chat_template(message, add_generation_prompt=True, tokenize=False)
# Create pipeline
pipeline = transformers.pipeline(
"text-generation",
model=new_model,
tokenizer=tokenizer
)
# Generate text
sequences = pipeline(
prompt,
do_sample=True,
temperature=0.7,
top_p=0.9,
num_return_sequences=1,
max_length=200,
)
print(sequences[0]['generated_text'])
```
### Limitations
This Distilucie model is a quick demonstration that the Lucie foundation model can be easily fine-tuned to achieve compelling performance.
It does not have any moderation mechanism.
- **Developed by:** Jonathan Pacifico, 2025
- **Model type:** LLM
- **Language(s) (NLP):** French, English
- **License:** Apache-2.0 |