Enrico Casini

@ico_chico

Scaling Machine Learning Pipelines. Making everything AI accessible .

Vrijeme pridruživanja: listopad 2009.

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  1. proslijedio/la je Tweet
    prije 14 sati

    How Discord went from millisecond latencies to microseconds by switching from Go to and Tokio

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  2. proslijedio/la je Tweet
    31. sij

    Transformers 2.4.0 is out 🤗 - Training transformers from scratch is now supported - New models, including *FlauBERT*, Dutch BERT, *UmBERTo* - Revamped documentation - First multi-modal model, MMBT from , text & images Bye bye Python 2 🙃

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  3. proslijedio/la je Tweet
    21. sij

    🥳 just released its top 50 start-ups to watch in 2020 with Streamlit on the list. The full list is below 👇

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  4. proslijedio/la je Tweet
    22. sij

    The fantastic & from will discuss large state-of-the-art NLP models in production tomorrow at . Join us if you're in NYC or mention your friends who could be interested!

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  5. proslijedio/la je Tweet
    20. sij

    I wrote a post for the Stack Overflow blog: What is Rust and why is it so popular?

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  6. proslijedio/la je Tweet
    21. sij

    Tokio v0.2.10 is out. The release includes a task-local storage solution that supports multiplexing futures on a single runtime task and a `StreamExt::collect()` implementation that works with `Bytes`

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  7. 14. sij

    “To the untrained eye, randomness appears as regularity or tendency to cluster.” William Feller

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  8. proslijedio/la je Tweet
    2. pro 2019.

    Finally finished the write-up of our ML experiments from - a 25x speedup is way more than we were expecting! Beyond the raw numbers, a long read on Python, , the scientific computing space and its outlook in the next few years.

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  9. proslijedio/la je Tweet
    8. sij

    Daniel quit his job as a web developer and structured his own learning plan to break into AI. Now he's the first MLE at a startup building an NLP-powered chatbot. Read Daniel's advice for getting started:

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  10. proslijedio/la je Tweet
    10. sij

    Repository and doc: To install: - Rust: - Python: pip install tokenizers - Node: npm install tokenizers

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  11. proslijedio/la je Tweet
    10. sij

    Now that neural nets have fast implementations, a bottleneck in pipelines is tokenization: strings➡️model inputs. Welcome 🤗Tokenizers: ultra-fast & versatile tokenization led by : -encode 1GB in 20sec -BPE/byte-level-BPE/WordPiece/SentencePiece... -python/js/rust...

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  12. proslijedio/la je Tweet
    8. sij

    These options break my brain every time.

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  13. proslijedio/la je Tweet
    5. sij

    NLP Year in Review — 2019 An extensive list of interesting publications, creative and societal applications, tools and datasets, articles, and resources of 2019 by .

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  14. proslijedio/la je Tweet
    29. pro 2019.

    Interested in for Italian? We release our cased and uncased BERT models for Italian 🥳 Use our models with the awesome🤗/ Transformers library from :

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  15. proslijedio/la je Tweet
    29. pro 2019.

    ┏━━┓┏━━┓┏━━┓┏━━┓ ┗━┓┃┃┏┓┃┗━┓┃┃┏┓┃ ┏━┛┃┃┃┃┃┏━┛┃┃┃┃┃ Solving Natural Language Processing! ┃┏━┛┃┃┃┃┃┏━┛┃┃┃┃ ┃┗━┓┃┗┛┃┃┗━┓┃┗┛┃ ┗━━┛┗━━┛┗━━┛┗━━┛

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  16. proslijedio/la je Tweet
    23. pro 2019.

    New NLP News: 2020 NLP wish lists, HuggingFace + fastai, NeurIPS 2019, GPT-2 things, Machine Learning Interviews via

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  17. 21. pro 2019.

    Why the Kotlin/Native memory model cannot hold. by Salomon Brys

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  18. 18. pro 2019.

    Scaling a massive State-of-the-Art Deep Learning model in production by

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  19. proslijedio/la je Tweet
    14. pro 2019.

    's f-strings are amazingly fast! f'{s} {t}' # 78.2 ns s + ' ' + t # 104 ns ' '.join((s, t)) # 135 ns '%s %s' % (s, t) # 188 ns '{} {}'.format(s, t) # 283 ns Template('$s ').substitute(s=s, t=t) # 898 ns

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  20. proslijedio/la je Tweet
    12. pro 2019.

    From today to January 10 is free to use for any shopping task – both online and in stores. Just call an agent and ask to activate the “Free Shopping” promotion. Happy shopping!

    A tall stack of brown cardboard packages stands outside a building painted in a vibrant "Aira" blue. A white Aira logo is in the top right corner of the picture.
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