Super-squash branch 'main' using huggingface_hub

Co-authored-by: hysts <[email protected]>
Co-authored-by: Xenova <[email protected]>

.gitattributes

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README.md

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+---
+title: Gemma 2 2B Neogenesis ITA
+emoji: 💎💬🇮🇹
+colorFrom: indigo
+colorTo: pink
+sdk: gradio
+sdk_version: 5.12.0
+app_file: app.py
+pinned: false
+short_description: Chat with an Italian Small Model
+---

app.py

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+import os
+from threading import Thread
+from typing import Iterator
+
+import gradio as gr
+import spaces
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
+
+DESCRIPTION = """\
+# Gemma 2 2B Neogenesis ITA 💎 💬 🇮🇹
+
+Fine-tuned version of Google/gemma-2-2b-it to improve the performance on the Italian language.
+Small (2.6 B parameters) but good model, with 8k context length.
+
+[🪪 **Model card**](https://huggingface.co/anakin87/gemma-2-2b-neogenesis-ita)
+TODO: add Kaggle link
+"""
+
+MAX_MAX_NEW_TOKENS = 2048
+DEFAULT_MAX_NEW_TOKENS = 1024
+MAX_INPUT_TOKEN_LENGTH = int(os.getenv("MAX_INPUT_TOKEN_LENGTH", "4096"))
+
+device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
+
+model_id = "anakin87/gemma-2-2b-neogenesis-ita"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    device_map="auto",
+    torch_dtype=torch.bfloat16,
+)
+model.config.sliding_window = 4096
+model.eval()
+
+
+@spaces.GPU
+def generate(
+    message: str,
+    chat_history: list[dict],
+    max_new_tokens: int = 1024,
+    temperature: float = 0.6,
+    top_p: float = 0.9,
+    top_k: int = 50,
+    repetition_penalty: float = 1.2,
+) -> Iterator[str]:
+    conversation = chat_history.copy()
+    conversation.append({"role": "user", "content": message})
+
+    input_ids = tokenizer.apply_chat_template(conversation, add_generation_prompt=True, return_tensors="pt")
+    if input_ids.shape[1] > MAX_INPUT_TOKEN_LENGTH:
+        input_ids = input_ids[:, -MAX_INPUT_TOKEN_LENGTH:]
+        gr.Warning(f"Trimmed input from conversation as it was longer than {MAX_INPUT_TOKEN_LENGTH} tokens.")
+    input_ids = input_ids.to(model.device)
+
+    streamer = TextIteratorStreamer(tokenizer, timeout=20.0, skip_prompt=True, skip_special_tokens=True)
+    generate_kwargs = dict(
+        {"input_ids": input_ids},
+        streamer=streamer,
+        max_new_tokens=max_new_tokens,
+        do_sample=True,
+        top_p=top_p,
+        top_k=top_k,
+        temperature=temperature,
+        num_beams=1,
+        repetition_penalty=repetition_penalty,
+    )
+    t = Thread(target=model.generate, kwargs=generate_kwargs)
+    t.start()
+
+    outputs = []
+    for text in streamer:
+        outputs.append(text)
+        yield "".join(outputs)
+
+
+chat_interface = gr.ChatInterface(
+    fn=generate,
+    additional_inputs=[
+        gr.Slider(
+            label="Max new tokens",
+            minimum=1,
+            maximum=MAX_MAX_NEW_TOKENS,
+            step=1,
+            value=DEFAULT_MAX_NEW_TOKENS,
+        ),
+        gr.Slider(
+            label="Temperature",
+            minimum=0.1,
+            maximum=4.0,
+            step=0.1,
+            value=0.6,
+        ),
+        gr.Slider(
+            label="Top-p (nucleus sampling)",
+            minimum=0.05,
+            maximum=1.0,
+            step=0.05,
+            value=0.9,
+        ),
+        gr.Slider(
+            label="Top-k",
+            minimum=1,
+            maximum=1000,
+            step=1,
+            value=50,
+        ),
+        gr.Slider(
+            label="Repetition penalty",
+            minimum=1.0,
+            maximum=2.0,
+            step=0.05,
+            value=1.2,
+        ),
+    ],
+    stop_btn=None,
+    examples=[
+        ["Ciao! Come stai?"],
+        ["Pro e contro di una relazione a lungo termine. Elenco puntato con max 3 pro e 3 contro sintetici."],
+        ["Quante ore impiega un uomo per mangiare un elicottero?"],
+        ["Come si apre un file JSON in Python?"],
+        ["Fammi un elenco puntato dei pro e contro di vivere in Italia. Massimo 2 pro e 2 contro."],
+        ["Inventa una breve storia con animali sul valore dell'amicizia."],
+        ["Scrivi un articolo di 100 parole sui 'Benefici dell'open-source nella ricerca sull'intelligenza artificiale'"],
+        ["Can you explain briefly to me what is the Python programming language?"],
+        ["How many hours does it take a man to eat a Helicopter?"],
+        ["Write a 100-word article on 'Benefits of Open-Source in AI research'"],
+    ],
+    cache_examples=False,
+    type="messages",
+)
+
+fonts = {"font":[gr.themes.GoogleFont("Source Sans Pro"), "ui-sans-serif", "system-ui", "sans-serif"],
+        "font_mono": [gr.themes.GoogleFont("IBM Plex Mono"),  "ui-monospace", "Consolas", "monospace"]}
+
+with gr.Blocks(css_paths="style.css", fill_height=True, theme=gr.themes.Soft(**fonts)) as demo:
+    gr.Markdown(DESCRIPTION)
+    gr.DuplicateButton(value="Duplicate Space for private use", elem_id="duplicate-button")
+    chat_interface.render()
+
+if __name__ == "__main__":
+    demo.queue(max_size=20).launch()

requirements.txt

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+accelerate
+transformers>=4.44.2

style.css

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+h1 {
+  text-align: center;
+  display: block;
+}
+
+#duplicate-button {
+  margin: auto;
+  color: #fff;
+  background: #1565c0;
+  border-radius: 100vh;
+}