Dicta-IL's dictalm2.0-instruct

README.md

@@ -1,13 +1,19 @@
 ---
-title: Dictalm2.0 Instruct
-emoji: 👁
-colorFrom: gray
+title: Dicta-IL's dictalm2.0-instruct
+emoji: 🕎
+colorFrom: blue
 colorTo: gray
 sdk: gradio
-sdk_version: 4.28.3
+sdk_version: 4.28.2
 app_file: app.py
 pinned: false
 license: apache-2.0
+suggested_hardware: a10g-small
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Dicta-IL's dictalm2.0-instruct
+
+dictalm2.0-instruct was introduced in [this Facebook post](https://www.facebook.com/groups/MDLI1/posts/2704204053076959//).
+
+Please, check the [original model card](https://huggingface.co/dicta-il/dictalm2.0-instruct) and [their official blog post](https://dicta.org.il/dicta-lm) for more details.
+You can see the other Hebrew models by Dicta-IL [here](https://huggingface.co/dicta-il)

app.py

@@ -0,0 +1,148 @@
+import os
+from threading import Thread
+from typing import Iterator
+
+import gradio as gr
+import spaces
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
+
+MAX_MAX_NEW_TOKENS = 1024
+DEFAULT_MAX_NEW_TOKENS = 256
+MAX_INPUT_TOKEN_LENGTH = 1024
+
+DESCRIPTION = """\
+# Dicta-IL's dictalm2.0-instruct
+
+dictalm2.0-instruct was introduced in [this Facebook post](https://www.facebook.com/groups/MDLI1/posts/2704204053076959//).
+
+Please, check the [original model card](https://huggingface.co/dicta-il/dictalm2.0-instruct) and [their official blog post](https://dicta.org.il/dicta-lm) for more details.
+You can see the other Hebrew models by Dicta-IL [here](https://huggingface.co/dicta-il)
+
+"""
+
+LICENSE = """
+<p/>
+
+---
+A derivative work of [mistral-7b](https://mistral.ai/news/announcing-mistral-7b/) by Mistral-AI.
+The model and space are released under the Apache 2.0 license
+"""
+
+if not torch.cuda.is_available():
+    DESCRIPTION += "\n<p>Running on CPU 🥶 This demo does not work on CPU.</p>"
+
+
+if torch.cuda.is_available():
+    model_id = "dicta-il/dictalm2.0-instruct"    
+    model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto", torch_dtype=torch.bfloat16, low_cpu_mem_usage=True)
+    tokenizer_id = "dicta-il/dictalm2.0-instruct"
+    tokenizer = AutoTokenizer.from_pretrained(tokenizer_id)
+    tokenizer.use_default_system_prompt = False
+        
+
+@spaces.GPU
+def generate(
+    message: str,
+    chat_history: list[tuple[str, str]],
+    max_new_tokens: int = 1024,
+    temperature: float = 0.6,
+    top_p: float = 0.9,
+    top_k: int = 50,
+    repetition_penalty: float = 1.4,
+) -> Iterator[str]:
+    conversation = []
+    for user, assistant in chat_history:
+        conversation.extend([{"role": "user", "content": user}, {"role": "assistant", "content": assistant}])
+    conversation.append({"role": "user", "content": message})
+
+    input_ids = tokenizer.apply_chat_template(conversation, 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=10.0, 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,
+        pad_token_id = tokenizer.eos_token_id,
+        repetition_penalty=repetition_penalty,
+        no_repeat_ngram_size=5,
+        early_stopping=True,
+    )
+    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,
+    chatbot=gr.Chatbot(rtl=True, show_copy_button=True),
+    textbox=gr.Textbox(text_align = 'right', rtl = True),
+    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=0.3,
+        ),
+        gr.Slider(
+            label="Top-p (nucleus sampling)",
+            minimum=0.05,
+            maximum=1.0,
+            step=0.05,
+            value=0.3,
+        ),
+        gr.Slider(
+            label="Top-k",
+            minimum=1,
+            maximum=1000,
+            step=1,
+            value=30,
+        ),
+        gr.Slider(
+            label="Repetition penalty",
+            minimum=1.0,
+            maximum=2.0,
+            step=0.05,
+            value=1.4,
+        ),
+    ],
+    stop_btn=None,
+    examples=[
+        ["מתכון לעוגת שוקולד:"],
+        ["השלם את הסיפור הקצר הבא:\n האיש האחרון בעולם ישב לבד בחדרו, כשלפתע נשמעה"],
+        ["מהי שפת התכנות פייתון?"],
+        ["סכם בקצרה את העלילה של סינדרלה"],
+        ["שאלה: מהי עיר הבירה של מדינת ישראל?\nתשובה:"],
+        ["שאלה: אני ממש עייף, מה כדאי לי לעשות?\nתשובה:"],
+    ],
+)
+
+with gr.Blocks(css="style.css") as demo:
+    gr.Markdown(DESCRIPTION)
+    gr.DuplicateButton(value="Duplicate Space for private use", elem_id="duplicate-button")
+    chat_interface.render()
+    gr.Markdown(LICENSE)
+
+if __name__ == "__main__":
+    demo.queue(max_size=20).launch()

requirements.txt

@@ -0,0 +1,9 @@
+accelerate==0.28.0
+bitsandbytes==0.43.0
+gradio==4.28.2
+scipy==1.12.0
+sentencepiece==0.2.0
+spaces==0.26.2
+torch==2.1.1
+transformers==4.40.1
+tokenizers==0.19.1

style.css

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+h1 {
+  text-align: center;
+  display: block;
+}
+
+#duplicate-button {
+  margin: auto;
+  color: white;
+  background: #1565c0;
+  border-radius: 100vh;
+}
+
+.contain {
+  max-width: 900px;
+  margin: auto;
+  padding-top: 1.5rem;
+}