71 lines
2.4 KiB
Markdown
71 lines
2.4 KiB
Markdown
|
---
|
||
|
|
license: gemma
|
||
|
|
language:
|
||
|
|
- ar
|
||
|
|
base_model:
|
||
|
|
- unsloth/gemma-2-2b-it
|
||
|
|
library_name: transformers
|
||
|
|
---
|
||
|
|
**Model Card: TunChat-V0.2**
|
||
|
|
|
||
|
|
**Model Overview:**
|
||
|
|
- **Model Name:** TunChat-V0.2
|
||
|
|
- **Model Size:** 2B parameters
|
||
|
|
- **Instruction-Tuned:** Yes
|
||
|
|
- **Language:** Tunisian Dialect
|
||
|
|
- **Use Case Focus:** Conversational exchanges, translation, summarization, content generation, and cultural research.
|
||
|
|
|
||
|
|
**Model Description:**
|
||
|
|
TunChat-V0.2 is a 2-billion parameter language model specifically instruction-tuned for the Tunisian dialect. It is designed to handle tasks such as conversational exchanges, informal text summarization, and culturally-aware content generation. The model is optimized to understand and generate text in Tunisian Dialect, enabling enhanced performance for applications targeting Tunisian users.
|
||
|
|
|
||
|
|
**Intended Use:**
|
||
|
|
- Conversational agents and chatbots operating in Tunisian Dialect.
|
||
|
|
- Translation, summarization, and content generation in informal Tunisian dialect.
|
||
|
|
- Supporting cultural research related to Tunisian language and heritage.
|
||
|
|
|
||
|
|
**How to Use:**
|
||
|
|
```python
|
||
|
|
import torch
|
||
|
|
from transformers import pipeline
|
||
|
|
|
||
|
|
pipe = pipeline(
|
||
|
|
"text-generation",
|
||
|
|
model="saifamdouni/TunChat-V0.2",
|
||
|
|
model_kwargs={"torch_dtype": torch.bfloat16},
|
||
|
|
device="cuda" # replace with "mps" to run on a Mac device
|
||
|
|
)
|
||
|
|
|
||
|
|
messages = [
|
||
|
|
{"role": "user", "content": 'شكون صنعك'},
|
||
|
|
]
|
||
|
|
|
||
|
|
outputs = pipe(messages,
|
||
|
|
max_new_tokens=2048,
|
||
|
|
do_sample=True,
|
||
|
|
top_p=0.95,
|
||
|
|
temperature=0.7,
|
||
|
|
top_k=50)
|
||
|
|
assistant_response = outputs[0]["generated_text"][-1]["content"].strip()
|
||
|
|
print(assistant_response)
|
||
|
|
```
|
||
|
|
|
||
|
|
>صنعوني جماعة من المهندسين والمطورين التوانسة. يحبوا يطوّروا الذكاء الاصطناعي في تونس و يسهلوا استخدامه باللهجة متاعنا.
|
||
|
|
|
||
|
|
|
||
|
|
**Quantized Versions:**
|
||
|
|
- GGUF quantized versions will be released later.
|
||
|
|
|
||
|
|
**Training Dataset:**
|
||
|
|
- Tun-SFT dataset (to be released later):
|
||
|
|
- A mix between organically collected and synthetically generated data
|
||
|
|
|
||
|
|
**Limitations and Ethical Considerations:**
|
||
|
|
- The model may occasionally produce incorrect or biased responses.
|
||
|
|
- The model may occasionally produce culturally inappropriate responses.
|
||
|
|
- It may not perform optimally on formal Tunisian Arabic texts.
|
||
|
|
|
||
|
|
**Future Plans:**
|
||
|
|
- Release of GGUF quantized versions.
|
||
|
|
- Open-source availability of the Tun-SFT dataset.
|
||
|
|
|
||
|
|
**Author:** Saif Eddine Amdouni
|