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Model: saifamdouni/TunCHAT-V0.2
Source: Original Platform

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README.md

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+---
+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

config.json

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+{
+  "_name_or_path": "unsloth/gemma-2-2b-it",
+  "architectures": [
+    "Gemma2ForCausalLM"
+  ],
+  "attention_bias": false,
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+  "cache_implementation": "hybrid",
+  "eos_token_id": [
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+    107
+  ],
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+  "model_type": "gemma2",
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+  "rope_scaling": null,
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+  "sliding_window": 4096,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.47.1",
+  "unsloth_version": "2024.12.4",
+  "use_cache": true,
+  "vocab_size": 256000
+}

generation_config.json

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+{
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+  "bos_token_id": 2,
+  "cache_implementation": "hybrid",
+  "eos_token_id": [
+    1,
+    107
+  ],
+  "max_length": 8192,
+  "pad_token_id": 0,
+  "transformers_version": "4.47.1"
+}

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