初始化项目，由ModelHub XC社区提供模型

Model: rasyosef/Llama-3.2-1B-Amharic
Source: Original Platform

README.md

@@ -0,0 +1,59 @@
+---
+widget:
+- text: አዲስ አበባ
+  example_title: Example 1
+- text: በኢንግሊዝ ፕሪምየር ሊግ
+  example_title: Example 2
+- text: ዶናልድ ትራምፕ
+  example_title: Example 3
+language:
+- am
+metrics:
+- perplexity
+library_name: transformers
+pipeline_tag: text-generation
+base_model:
+- meta-llama/Llama-3.2-1B-Instruct
+---
+
+# Llama-3.2-Amharic-1B
+
+This model is a version of Meta's [Llama-3.2-1B](https://huggingface.co/meta-llama/Llama-3.2-1B) decoder transformer model that was continuously pretrained on an Amharic text corpus. 
+
+- 16k new amharic tokens were added to the Llama 3.2 tokenizer and the embdedding layer of the model was resized accordingly. 
+- The model was then trained on **300 million tokens** of **Amharic** text.
+- This is a base model. The Amharic instruction following version is [Llama-3.2-1B-Amharic-Instruct](https://huggingface.co/rasyosef/Llama-3.2-1B-Amharic-Instruct)
+
+### How to use
+First, you need to install the latest version of transformers
+```
+pip install -Uq transformers
+```
+
+You can use this model directly with a pipeline for text generation:
+
+```python
+from transformers import pipeline
+
+llama_am = pipeline(
+    "text-generation",
+    model="rasyosef/Llama-3.2-1B-Amharic",
+    device_map="auto"
+  )
+
+prompt = "በኢንግሊዝ ፕሪምየር ሊግ"
+llama_am(
+    prompt,
+    max_new_tokens=128,
+    temperature=0.3,
+    do_sample=True,
+    top_k=8,
+    top_p=0.8,
+    repetition_penalty=1.05
+  )
+```
+
+Output:
+```python
+[{'generated_text': 'በኢንግሊዝ ፕሪምየር ሊግ የ2017/18 የውድድር ዘመን ላይ ተሳታፊ የሆነው ሊቨርፑል ትናንት ምሽት 3 :45 ላይ ከዌስትሀም ዩናይትድ ጋር ባደረገው ጨዋታ በ2 ለ 1 ውጤት ተሸንፏል ።'}]
+```