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Running
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Hebrew-Mistral-7B
Browse files
README.md
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---
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title: Hebrew
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sdk: gradio
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sdk_version: 4.28.
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app_file: app.py
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pinned: false
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---
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---
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title: Yam-Peleg Hebrew-Mistral-7B
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emoji: ๐
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colorFrom: blue
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colorTo: gray
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sdk: gradio
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sdk_version: 4.28.2
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app_file: app.py
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pinned: false
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license: apache-2.0
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suggested_hardware: a10g-small
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---
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# Yam-Peleg's Hebrew-Mistral-7B
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Hebrew-Mistral-7B was introduced in [this Facebook post](https://www.facebook.com/groups/MDLI1/posts/2701023256728372/).
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Please, check the [original model card](https://huggingface.co/yam-peleg/Hebrew-Mistral-7B) for more details.
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You can see the other Hebrew models by Yam [here](https://huggingface.co/collections/yam-peleg/hebrew-models-65e957875324e2b9a4b68f08)
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app.py
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import os
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from threading import Thread
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from typing import Iterator
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import gradio as gr
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import spaces
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
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MAX_MAX_NEW_TOKENS = 1024
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DEFAULT_MAX_NEW_TOKENS = 256
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MAX_INPUT_TOKEN_LENGTH = 512
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DESCRIPTION = """\
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# Yam-Peleg's Hebrew-Mistral-7B
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Hebrew-Mistral-7B was introduced in [this Facebook post](https://www.facebook.com/groups/MDLI1/posts/2701023256728372/).
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Please, check the [original model card](https://huggingface.co/yam-peleg/Hebrew-Mistral-7B) for more details.
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You can see the other Hebrew models by Yam [here](https://huggingface.co/collections/yam-peleg/hebrew-models-65e957875324e2b9a4b68f08)
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# Note: Use this model for only for completing sentences.
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## While the user interface is of a chatbot for convenience, this is a base model and is not fine-tuned for chatbot tasks or instruction following tasks. As such, the model is not provided a chat history and will complete your text based on the last given prompt only.
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"""
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LICENSE = """
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<p/>
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---
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A derivative work of [mistral-7b](https://mistral.ai/news/announcing-mistral-7b/) by Mistral-AI.
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The model and space are released under the Apache 2.0 license
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"""
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if not torch.cuda.is_available():
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DESCRIPTION += "\n<p>Running on CPU ๐ฅถ This demo does not work on CPU.</p>"
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if torch.cuda.is_available():
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model_id = "yam-peleg/Hebrew-Mistral-7B"
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model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto", torch_dtype=torch.bfloat16, low_cpu_mem_usage=True)
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tokenizer_id = "yam-peleg/Hebrew-Mistral-7B"
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tokenizer = AutoTokenizer.from_pretrained(tokenizer_id)
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@spaces.GPU
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def generate(
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message: str,
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chat_history: list[tuple[str, str]],
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max_new_tokens: int = 1024,
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temperature: float = 0.2,
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top_p: float = 0.7,
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top_k: int = 30,
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repetition_penalty: float = 1.0,
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) -> Iterator[str]:
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input_ids = tokenizer([message], return_tensors="pt").input_ids
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if input_ids.shape[1] > MAX_INPUT_TOKEN_LENGTH:
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input_ids = input_ids[:, -MAX_INPUT_TOKEN_LENGTH:]
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gr.Warning(f"Trimmed input from conversation as it was longer than {MAX_INPUT_TOKEN_LENGTH} tokens.")
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input_ids = input_ids.to(model.device)
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streamer = TextIteratorStreamer(tokenizer, timeout=10.0, skip_prompt=True, skip_special_tokens=True)
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generate_kwargs = dict(
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{"input_ids": input_ids},
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streamer=streamer,
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max_new_tokens=max_new_tokens,
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do_sample=True,
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top_p=top_p,
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top_k=top_k,
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temperature=temperature,
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num_beams=1,
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pad_token_id = tokenizer.eos_token_id,
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repetition_penalty=repetition_penalty,
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no_repeat_ngram_size=5,
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early_stopping=True,
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)
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t = Thread(target=model.generate, kwargs=generate_kwargs)
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t.start()
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outputs = []
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for text in streamer:
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outputs.append(text)
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yield "".join(outputs)
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chat_interface = gr.ChatInterface(
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fn=generate,
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chatbot=gr.Chatbot(rtl=True, show_copy_button=True),
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textbox=gr.Textbox(text_align = 'right', rtl = True),
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additional_inputs=[
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gr.Slider(
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label="Max new tokens",
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minimum=1,
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maximum=MAX_MAX_NEW_TOKENS,
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step=1,
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value=DEFAULT_MAX_NEW_TOKENS,
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),
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gr.Slider(
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label="Temperature",
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minimum=0.1,
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maximum=4.0,
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step=0.1,
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value=0.3,
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),
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gr.Slider(
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label="Top-p (nucleus sampling)",
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minimum=0.05,
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maximum=1.0,
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step=0.05,
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value=0.3,
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),
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gr.Slider(
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label="Top-k",
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minimum=1,
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maximum=1000,
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step=1,
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value=30,
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),
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],
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stop_btn=None,
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examples=[
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["ืืชืืื ืืขืืืช ืฉืืงืืื:"],
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["ืืืืฉ ืืืืจืื ืืขืืื ืืฉื ืืื ืืืืจื, ืืฉืืคืชืข ื ืฉืืขื"],
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["ืฉืคืช ืืชืื ืืช ืคืืืืื ืืื"],
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["ืืขืืืื ืฉื ืกืื ืืจืื"],
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["ืฉืืื: ืืื ืขืืจ ืืืืจื ืฉื ืืืื ืช ืืฉืจืื?\nืชืฉืืื:"],
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["ืฉืืื: ืื ื ืืืฉ ืขืืืฃ, ืื ืืืื ืื ืืขืฉืืช?\nืชืฉืืื:"],
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],
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)
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with gr.Blocks(css="style.css") as demo:
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gr.Markdown(DESCRIPTION)
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gr.DuplicateButton(value="Duplicate Space for private use", elem_id="duplicate-button")
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chat_interface.render()
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gr.Markdown(LICENSE)
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if __name__ == "__main__":
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demo.queue(max_size=20).launch()
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requirements.txt
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accelerate==0.28.0
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bitsandbytes==0.43.0
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gradio==4.28.2
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scipy==1.12.0
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sentencepiece==0.2.0
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spaces==0.26.2
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torch==2.1.1
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transformers==4.40.1
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tokenizers==0.19.1
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style.css
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h1 {
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text-align: center;
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display: block;
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}
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#duplicate-button {
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margin: auto;
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color: white;
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background: #1565c0;
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border-radius: 100vh;
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}
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.contain {
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max-width: 900px;
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margin: auto;
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padding-top: 1.5rem;
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}
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