Update README.md

README.md

@@ -1,7 +1,7 @@
 ---
 base_model: inceptionai/jais-adapted-7b-chat
 language:
-- en
+- ar
 license: apache-2.0
 tags:
 - text-generation-inference
@@ -9,6 +9,9 @@ tags:
 - unsloth
 - llama
 - trl
+datasets:
+- Wajdi1976/Tunisian_Derja_Dataset
+library_name: transformers
 ---
 
 # Uploaded  model
@@ -16,7 +19,62 @@ tags:
 - **Developed by:** Wajdi1976
 - **License:** apache-2.0
 - **Finetuned from model :** inceptionai/jais-adapted-7b-chat
+- 
+## Usage
+Below we share some code snippets on how to get quickly started with running the model. First, install the Transformers library with:
+
+```sh
+pip install unsloth
+```
+### First, Load the Model
+```python
+from unsloth import FastLanguageModel
+import torch
+max_seq_length = 600 # Choose any! We auto support RoPE Scaling internally!
+dtype = None # None for auto detection. Float16 for Tesla T4, V100, Bfloat16 for Ampere+
+load_in_4bit = True # Use 4bit quantization to reduce memory usage. Can be False.
+model, tokenizer = FastLanguageModel.from_pretrained(
+    model_name = "Wajdi1976/jais_arabic_tunisien_derija",
+    max_seq_length = max_seq_length,
+    dtype = dtype,
+    load_in_4bit = load_in_4bit,    
+)
+```
+
+### Second, Try the model 
+```python
+prompt_ar=" يمكنك الإجابة باللهجة التونسية فقط.\n\nأكمل المحادثة أدناه بين [|Human|] و [|AI|]:\n### Input: [|Human|] {Question}\n### Response: [|AI|]"
+device = "cuda" if torch.cuda.is_available() else "cpu"
+FastLanguageModel.for_inference(model)
+if tokenizer.pad_token is None:
+    tokenizer.pad_token = tokenizer.eos_token
+def get_response(text, tokenizer=tokenizer, model=model):
+    tokenized = tokenizer(text, return_tensors="pt")
+    input_ids, attention_mask = tokenized['input_ids'].to(device), tokenized['attention_mask'].to(device)
+    input_len = input_ids.shape[-1]
+    generate_ids = model.generate(
+        input_ids,
+        attention_mask=attention_mask,
+        top_p=1,
+        temperature=0.3,
+        max_length=600,
+        min_length=input_len + 4,
+        repetition_penalty=1.2,
+        do_sample=True,
+        pad_token_id=tokenizer.pad_token_id
+    )
+    response = tokenizer.batch_decode(
+        generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=True
+    )[0]
+    response = response.split("### Response :")[-1].lstrip()
+    return response
+
+ques = "  احكي معايا باللهجة التونسية"
+text = prompt_ar.format_map({'Question': ques})
+print(get_response(text))
+```
+- Response:  بالطبع نجم نجاوب على سؤالك واللهجه التونسية هي نوع من اللهجات اللي تتكلم في بلاد اسمها تونس كيفما فما برشا لهجات مختلفة كيما الإنجليزية أو الإسبانية الناس في العالم يتكلموا لغات متنوعة أما اللهجة التونسى هيا الطريقة الخاصة بالكلام للناس في البلاد هذيك يعني كان تسألني سؤال بالهججه تونسي نحب نعاونك باش نفهموه 
 
 This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
 
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)