Initial commit with Selene-1-Mini-Llama implementation

.python-version

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+3.12

app.py

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+from transformers import AutoModelForCausalLM, AutoTokenizer
+import gradio as gr
+import spaces
+import torch
+
+model_id = "AtlaAI/Selene-1-Mini-Llama-3.1-8B"
+
+model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto")
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+
+@spaces.GPU
+def generate_response(prompt):
+    messages = [{"role": "user", "content": prompt}]
+    text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+    model_inputs = tokenizer([text], return_tensors="pt").to("cuda")
+    
+    generated_ids = model.generate(
+        model_inputs.input_ids,
+        max_new_tokens=512,
+        do_sample=True
+    )
+    generated_ids = [output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)]
+    
+    response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+    return response
+
+demo = gr.Interface(
+    fn=generate_response,
+    inputs=gr.Textbox(label="プロンプトを入力してください"),
+    outputs=gr.Textbox(label="生成された応答"),
+    title="Selene-1-Mini-Llama-3.1-8B デモ",
+    description="プロンプトを入力すると、モデルが応答を生成します。"
+)
+
+if __name__ == "__main__":
+    demo.launch()

pyproject.toml

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+[project]
+name = "demo-atlaai-selene-1-mini-llama-3-1-8b"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.12"
+dependencies = [
+    "gradio>=5.13.2",
+    "spaces>=0.32.0",
+    "torch>=2.6.0",
+    "transformers>=4.48.1",
+]

requirements.txt

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+transformers
+torch
+gradio
+spaces