Update README.md

README.md

@@ -4,4 +4,41 @@ language:
 - tig
 base_model:
 - meta-llama/Llama-3.2-1B
----
+---
+
+import torch, logging
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+tig_model_path = "BeitTigreAI/tigre-llm-Llama3.2-1B"
+
+# Set the device for computation
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+# Load the tokenizer and model from the specified path
+tokenizer = AutoTokenizer.from_pretrained(tig_model_path)
+model = AutoModelForCausalLM.from_pretrained(tig_model_path, device_map="auto")
+model = model.to(device)
+
+# Suppress some of the logging for a cleaner output
+logging.getLogger("transformers").setLevel(logging.ERROR)
+
+# Example 1: Generate text in Tigre (written in Ethiopic script)
+prompt = "[tig_Ethi]መርሐበ ብኩም"
+inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+outputs = model.generate(**inputs, max_new_tokens=50)
+print("Tigre Output:")
+print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))
+
+# Example 2: Generate text in Arabic
+prompt = "ما الذي يميز لغة التغري؟"
+inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+outputs = model.generate(**inputs, max_new_tokens=40)
+print("\nArabic Output:")
+print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))
+
+# Example 3: Generate text in English
+prompt = "[eng_Latn] What is interesting about the Tigre language?"
+inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+outputs = model.generate(**inputs, max_new_tokens=40)
+print("\nEnglish Output:")
+print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))