Cloudera Fast Forward Labs

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Cloudera Fast Forward Labs is an applied machine learning research group.

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andrewrreed updated a Space over 2 years ago

cffl/Exploring_Intelligent_Writing_Assistance

andrewrreed updated a model over 2 years ago

cffl/bart-base-styletransfer-subjective-to-neutral

andrewrreed updated a model over 2 years ago

cffl/bert-base-styleclassification-subjective-neutral

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cffl's activity

andrewrreed

posted an update 30 days ago

Post

943

Trace LLM calls with Arize AI's Phoenix observability dashboards on Hugging Face Spaces! 🚀

✨ I just added a new recipe to the Open-Source AI Cookbook that shows you how to:
1️⃣ Deploy Phoenix on HF Spaces with persistent storage in a few clicks
2️⃣ Configure LLM tracing with the 𝗦𝗲𝗿𝘃𝗲𝗿𝗹𝗲𝘀𝘀 𝗜𝗻𝗳𝗲𝗿𝗲𝗻𝗰𝗲 𝗔𝗣𝗜
3️⃣ Observe multi-agent application runs with the CrewAI integration

𝗢𝗯𝘀𝗲𝗿𝘃𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗶𝘀 𝗰𝗿𝘂𝗰𝗶𝗮𝗹 for building robust LLM apps.

Phoenix makes it easy to visualize trace data, evaluate performance, and track down issues. Give it a try!

🔗 Cookbook recipe: https://huggingface.co/learn/cookbook/en/phoenix_observability_on_hf_spaces
🔗 Phoenix docs: https://docs.arize.com/phoenix

andrewrreed

posted an update 8 months ago

Post

2540

🔬 Open LLM Progress Tracker 🔬

Inspired by the awesome work from @mlabonne , I created a Space to monitor the narrowing gap between open and proprietary LLMs as scored by the LMSYS Chatbot Arena ELO ratings 🤗

The goal is to have a continuously updated place to easily visualize these rapidly evolving industry trends 🚀

🔗 Open LLM Progress Tracker: andrewrreed/closed-vs-open-arena-elo
🔗 Source of Inspiration: https://www.linkedin.com/posts/maxime-labonne_arena-elo-graph-updated-with-new-models-activity-7187062633735368705-u2jB/

2 replies

andrewrreed

posted an update 8 months ago

Post

2318

IMO, the "grounded generation" feature from Cohere's CommandR+ has flown under the radar...

For RAG use cases, responses directly include inline citations, making source attribution an inherent part of generation rather than an afterthought 😎

Who's working on an open dataset with this for the HF community to fine-tune with??

🔗CommandR+ Docs: https://docs.cohere.com/docs/retrieval-augmented-generation-rag

🔗Model on the 🤗 Hub: CohereForAI/c4ai-command-r-plus

1 reply

andrewrreed

posted an update 11 months ago

Post

🚀 It's now easier than ever to switch from OpenAI to open LLMs

Hugging Face's TGI now supports an OpenAI compatible Chat Completion API

This means you can transition code that uses OpenAI client libraries (or frameworks like LangChain 🦜 and LlamaIndex 🦙) to run open models by changing just two lines of code 🤗

⭐ Here's how:

from openai import OpenAI

# initialize the client but point it to TGI
client = OpenAI(
    base_url="<ENDPOINT_URL>" + "/v1/",  # replace with your endpoint url
    api_key="<HF_API_TOKEN>",  # replace with your token
)
chat_completion = client.chat.completions.create(
    model="tgi",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Why is open-source software important?"},
    ],
    stream=True,
    max_tokens=500
)

# iterate and print stream
for message in chat_completion:
    print(message.choices[0].delta.content, end="")