nlp-en-es (NLP en ES)

lewtun

posted an update 9 days ago

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We outperform Llama 70B with Llama 3B on hard math by scaling test-time compute 🔥

How? By combining step-wise reward models with tree search algorithms :)

We show that smol models can match or exceed the performance of their much larger siblings when given enough "time to think"

We're open sourcing the full recipe and sharing a detailed blog post.

In our blog post we cover:

📈 Compute-optimal scaling: How we implemented DeepMind's recipe to boost the mathematical capabilities of open models at test-time.

🎄 Diverse Verifier Tree Search (DVTS): An unpublished extension we developed to the verifier-guided tree search technique. This simple yet effective method improves diversity and delivers better performance, particularly at large test-time compute budgets.

🧭 Search and Learn: A lightweight toolkit for implementing search strategies with LLMs and built for speed with vLLM

Here's the links:

- Blog post: HuggingFaceH4/blogpost-scaling-test-time-compute

- Code: https://github.com/huggingface/search-and-learn

Enjoy!

2 replies

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mariagrandury

authored a paper 3 months ago

Evaluating Large Language Models with Tests of Spanish as a Foreign Language: Pass or Fail?

Paper • 2409.15334 • Published Sep 8

mariagrandury

authored a paper 5 months ago

The #Somos600M Project: Generating NLP resources that represent the diversity of the languages from LATAM, the Caribbean, and Spain

Paper • 2407.17479 • Published Jul 1

mrm8488

posted an update 6 months ago

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4674

🚨Exciting news for the Multilingual Synthetic Data Community!🚨

I’ve taken inspiration from the MAGPIE paper on Llama-3-8B-instruct and extended its capabilities. Here’s what’s new!

🗞 The MAGPIE paper showcased that if you use the instruction-tuned version (Llama-3-8B-instruct) to generate synthetic instructions and then fine-tune the base version (Llama-3-8B) on this dataset, you can improve even the it-tuned version

🤔 While reading a script by Sebastian Raschka, PhD, I wondered: Could these advancements be replicated in other languages? Specifically, could they benefit non-English datasets?

🎉 And the answer is YES! At least for Spanish. I've successfully adapted the techniques for Spanish, proving the model's flexibility and multilingual capabilities.

👩‍💻 To make this accessible, I created a basic script (heavily inspired by the Sebastian Raschka one) that allows you to generate similar datasets using ollama models (initially phi and llama3) automatically and upload it to the Hugging Face Hub!
[Script](https://gist.github.com/mrm8488/4650a5e3cc45523798a527a3446eb312)

🔍 Explore the datasets 📚 generated using our new script!

- [Llama-3-8B](https://huggingface.co/datasets/mrm8488/dataset_llama3_5000_samples_es_4231_filtered)
- [Phi-3-medium](https://huggingface.co/datasets/mrm8488/dataset_phi3-medium_5000_samples_es_3906_filtered)
- [Phi-3-mini](https://huggingface.co/datasets/mrm8488/dataset_phi3_5000_samples_es_3282_filtered)

Note: These datasets have basic filtering. Apply additional quality filters before using them to fine-tune large language models.

Inspiration and base script:
https://github.com/rasbt/LLMs-from-scratch/blob/main/ch07/05_dataset-generation/llama3-ollama.ipynb
https://www.linkedin.com/feed/update/urn:li:activity:7210982019751661568/

7 replies

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mariagrandury

authored a paper 6 months ago

Spanish and LLM Benchmarks: is MMLU Lost in Translation?

Paper • 2406.17789 • Published May 28

mrm8488

posted an update 8 months ago

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Working on a concept GPT-2 (small) that uses KANs instead of MLPs.
The ckpt and training code will be soon on the hub.

6 replies

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osanseviero

posted an update 8 months ago

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9814

Diaries of Open Source. Part 15 🤗

🕵️‍♀️Idefics 2 is out, a multimodal open-source model with very nice capabilities
Models, demo, and datasets: HuggingFaceM4/idefics2-661d1971b7c50831dd3ce0fe
Blog: https://hf.co/blog/idefics2

💾Snowflake released snowflake-arctic-embed, a family of powerful small embedding models
Model: Snowflake/snowflake-arctic-embed-m
Blog: https://www.snowflake.com/blog/introducing-snowflake-arctic-embed-snowflakes-state-of-the-art-text-embedding-family-of-models/

✨Pile-T5, EleutherAI's T5 model trained on 2T tokens
Blog: https://blog.eleuther.ai/pile-t5/
Models: EleutherAI/pile-t5-65a76a0d0022dd270b385a66
GitHub: https://github.com/EleutherAI/improved-t5

🤖CodeQwen1.5-7B base and chat models. Models trained on 3T tokens strong benchmark results for code generation, editing and SQL
Blog post: https://qwenlm.github.io/blog/codeqwen1.5/
Demo: Qwen/CodeQwen1.5-7b-Chat-demo
Models: Qwen/CodeQwen1.5-7B and Qwen/CodeQwen1.5-7B-Chat

Misc
🦉 DocOwl1.5: Unified Stucture Learning for OCR-free Document Understanding mPLUG/DocOwl
👀Cerule - a tiny Vision LM model Tensoic/Cerule-v0.1
ChemLLM - a LLM for chemistry and molecule science ⚗️https://hf.co/AI4Chem/ChemLLM-7B-Chat-1.5-DPO
Distil Whisper Large
📝New pdf/OCR datasets with 19 samples pixparse/pdf-document-ocr-datasets-660701430b0346f97c4bc628
🔥Gretel AI high quality text-to-sql synthetic dataset gretelai/synthetic_text_to_sql

4 replies

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lewtun

posted an update 9 months ago

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Introducing Zephyr 141B-A35B 🪁:

HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1

Yesterday, Mistral released their latest base model (via magnet link of course 😅) and the community quickly converted it to transformers format and pushed it to the Hub: mistral-community/Mixtral-8x22B-v0.1

Early evals of this model looked extremely strong, so we teamed up with Argilla and KAIST AI to cook up a Zephyr recipe with a few new alignment techniques that came out recently:

🧑‍🍳 Align the base model with Odds Ratio Preference Optimisation (ORPO). This novel algorithm developed by @JW17 and @nlee-208 and @j6mes and does not require an SFT step to achieve high performance and is thus much more computationally efficient than methods like DPO and PPO.

🦫 Use a brand new dataset of 7k high-quality, multi-turn preferences that has been developed by our friends at Argilla. To create this dataset, they took the excellent Capybara SFT dataset from @LDJnr LDJnr/Capybara and converted it into a preference dataset by augmenting the final turn with responses from new LLMs that were then ranked by GPT-4.

What we find especially neat about this approach is that training on 7k samples only takes ~1.3h on 4 H100 nodes, yet produces a model that is very strong on chat benchmarks like IFEval and BBH.

Kudos to @alvarobartt @JW17 and @nlee-208 for this very nice and fast-paced collab!

For more details on the paper and dataset, checkout our collection: HuggingFaceH4/zephyr-orpo-6617eba2c5c0e2cc3c151524

osanseviero

posted an update 9 months ago

Post

9271

Diaries of Open Source. Part 14 🤗

🔥CohereForAI releases Command R+, an open 104B model with:
- Tool usage capabilities
- Specialized in RAGs
- Multilingual
It's one of the first models to surpass GPT-4 in the lmsys arena, check it out!
Model: CohereForAI/c4ai-command-r-plus
Official demo: https://hf.co/spaces/CohereForAI/c4ai-command-r-plus
Quantized: CohereForAI/c4ai-command-r-plus-4bit

🎉Google releases a new version of their Gemma instruct models, with improved quality, nicer to converse, and a fancier RL algorithm. The model is similar to Llama 2 70B in the Chat Arena!
Models: google/gemma-release-65d5efbccdbb8c4202ec078b
Try it out in HuggingChat https://hf.co/chat/models/google/gemma-1.1-7b-it

🪄VoiceCraft, a speech editing and TTS SOTA open model
Paper: VoiceCraft: Zero-Shot Speech Editing and Text-to-Speech in the Wild (2403.16973)
Model: pyp1/VoiceCraft

💻Google released CodeGemma, a family of code generation, completion, and chat models
Blog post: https://hf.co/blog/codegemma
Models: google/codegemma-release-66152ac7b683e2667abdee11
Report: https://storage.googleapis.com/deepmind-media/gemma/codegemma_report.pdf

Misc models:
🦖T-Rex2, a very powerful object detection model for many applications https://github.com/IDEA-Research/T-Rex
👀 CT-RATE : A 3D dataset paired with text reports ibrahimhamamci/CT-RATE
🐙Octopus v2: a Gemma-based model trained for Android API - extremely fast, better than Llama+RAG, great results NexaAIDev/Octopus-v2

2 replies

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osanseviero

posted an update 9 months ago

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2279

Diaries of Open Source. Part 13 🤗

🤏Two different bitnet 1.5 open-source replications
Original paper: The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits (2402.17764)
1bitllm experiment: https://hf.co/blog/joey00072/experiments-with-bitnet-1-5
NousResearch experiment NousResearch/OLMo-Bitnet-1B

🥳Tiny and large multimodal models great for embeddings
GitHub: https://github.com/unum-cloud/uform
Encoders: https://hf.co/collections/unum-cloud/multimodal-encoders-660553903617c5297eb16838
ONNX weights: https://hf.co/collections/unum-cloud/uform-vl-english-large-onnx-66055a57c182d846f3bc1949

📜 SMPLer-X: Expressive Human Pose and Shape Estimation
Project website: https://caizhongang.com/projects/SMPLer-X/
Demo: caizhongang/SMPLer-X
Paper: SMPLer-X: Scaling Up Expressive Human Pose and Shape Estimation (2309.17448)

🧙GeoWizard: 3D Geometry Estimation
Project website: https://fuxiao0719.github.io/projects/geowizard/
Demo: lemonaddie/geowizard

Misc models and datasets
- Dolphin-2.8-mistral-7b-v0.2 cognitivecomputations/dolphin-2.8-mistral-7b-v02
- Hermes-2-Pro-11B, a self-frankenmerge 11B variant mattshumer/Hermes-2-Pro-11B
- Large conversational dataset based on Usenet data in the Italian language mii-community/UsenetArchiveIT-conversations

3 replies

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osanseviero

posted an update 9 months ago

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3528

Diaries of Open Source. Part 12 🤗

🚀Alibaba releases Qwen1.5-MoE-A2.7B, an interesting MoE with 2.7B activated parameters and 64 experts
Blog https://qwenlm.github.io/blog/qwen-moe/
Demo: Qwen/qwen1.5-MoE-A2.7B-Chat-demo
Models: https://hf.co/Qwen
GitHub: https://github.com/QwenLM/Qwen1.5

🎵VoiceCraft, SOTA speech editing and text to speech
GitHub: https://github.com/jasonppy/VoiceCraft
Model: pyp1/VoiceCraft

🐍 AI21Labs release Jamba, an SSM-Transformer, pretrained MoE which allows a large context window (256K) and high throughput
Blog https://www.ai21.com/blog/announcing-jamba
Model ai21labs/Jamba-v0.1

✨ Berkeley releases Starling-LM-7B, an RLHF-ed model, and -RM-34B, a Yi-based reward model very good for its size
Starling Beta: Nexusflow/Starling-LM-7B-beta
Starling RM: Nexusflow/Starling-RM-34B

🖥️Stability releases Stable Code Instruct 3B, an instruct model for code generation
Blog: https://stability.ai/news/introducing-stable-code-instruct-3b
Demo: stabilityai/stable-code-instruct-3b
Report: https://stability.ai/s/Stable_Code_TechReport_release.pdf

📚Common Corpus: the largest public domain dataset for training LLMs
Blog: https://hf.co/blog/Pclanglais/common-corpus
Dataset: https://hf.co/collections/PleIAs/common-corpus-65d46e3ea3980fdcd66a5613

Misc:
⚡GaLore: a very memory-efficient technique that allows pretraining models in consumer GPUs https://hf.co/blog/galore
Moirai
📈Moirai, foundation models for time series forecasting https://hf.co/collections/Salesforce/moirai-10-r-models-65c8d3a94c51428c300e0742
🔥 Mistral-ORPO-Capybara-7K, a high-quality Mistral fine-tune using ORPO, a new alignment technique kaist-ai/mistral-orpo-capybara-7k
🤯APISR, an anime super-resolution upscaling model HikariDawn/APISR

4 replies

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osanseviero

posted an update 9 months ago

Post

2068

Diaries of Open Source. Part 11 🚀

🚀Databricks release DBRX, potentially the best open access model! A 132B Mixture of Experts with 36B active params and trained on 12 trillion tokens
Blog: https://www.databricks.com/blog/introducing-dbrx-new-state-art-open-llm
Base and instruct models: databricks/dbrx-6601c0852a0cdd3c59f71962
Demo: databricks/dbrx-instruct

🤏1-bit and 2-bit quantization exploration using HQQ+
Blog post: https://mobiusml.github.io/1bit_blog/
Models: https://hf.co/collections/mobiuslabsgmbh/llama2-7b-hqq-6604257a96fc8b9c4e13e0fe
GitHub: https://github.com/mobiusml/hqq

📚Cosmopedia: a large-scale synthetic dataset for pre-training - it includes 25 billion tokens and 30 million files
Dataset: HuggingFaceTB/cosmopedia
Blog: https://hf.co/blog/cosmopedia

⭐Mini-Gemini: multi-modal VLMs, from 2B to 34B
Models: https://hf.co/collections/YanweiLi/mini-gemini-6603c50b9b43d044171d0854
Paper: Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models (2403.18814)
GitHub: https://github.com/dvlab-research/MiniGemini

🔥VILA - On Pre-training for VLMs
Models: Efficient-Large-Model/vila-on-pre-training-for-visual-language-models-65d8022a3a52cd9bcd62698e
Paper: VILA: On Pre-training for Visual Language Models (2312.07533)

Misc
👀 FeatUp: a framework for image features at any resolution: mhamilton723/FeatUp FeatUp: A Model-Agnostic Framework for Features at Any Resolution (2403.10516)
🍞ColBERTus Maxiums, a colbertialized embedding model mixedbread-ai/mxbai-colbert-large-v1
🖌️Semantic Palette, a new drawing paradigm ironjr/SemanticPalette
🧑‍⚕️HistoGPT, a vision model that generates accurate pathology reports marr-peng-lab/histogpt https://www.medrxiv.org/content/10.1101/2024.03.15.24304211v1

4 replies

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osanseviero

posted an update 9 months ago

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Diaries of Open Source. Part 10 🚀

🌼Marigold-LCM: A super fast SOTA Depth Estimator
Demo: prs-eth/marigold-lcm
Original paper: Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation (2312.02145)
Model: https://hf.co/prs-eth/marigold-lcm-v1-0

🌟Quiet-STaR: A self-teaching technique via internal monologue
Paper: Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking (2403.09629)
GitHub: https://github.com/ezelikman/quiet-star
Tweetutorial: https://twitter.com/ericzelikman/status/1768663835106513041

🖼️ WebSight v0.2: A image-to-code dataset containing tailwind CSS, images in screenshots, and more!
Dataset: HuggingFaceM4/WebSight
Paper: Unlocking the conversion of Web Screenshots into HTML Code with the WebSight Dataset (2403.09029)
Blog: https://hf.co/blog/websight

🕵️Agent-FLAN - effective agent tuning for LLMs
Paper: Agent-FLAN: Designing Data and Methods of Effective Agent Tuning for Large Language Models (2403.12881)
Model: internlm/Agent-FLAN-7b
Dataset: internlm/Agent-FLAN
Website: https://internlm.github.io/Agent-FLAN/

🔥HPT, a family of multimodal LLMs from HyperGAI
Blog post: https://hypergai.com/blog/introducing-hpt-a-family-of-leading-multimodal-llms
Model: HyperGAI/HPT
GitHub: https://github.com/hyperGAI/HPT

🌏Models and datasets around the world
- Tess-70B, a MiQu-70B fine-tune with high-quality data migtissera/Tess-70B-v1.6
- UNI, a model trained on 100 million pathology images from 100k+ slides MahmoodLab/UNI
- CONCH, a VLM trained on 1.17 million pathology image-text pairs MahmoodLab/CONCH

4 replies

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osanseviero

posted an update 9 months ago

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3268

Diaries of Open Source. Part 9!

⏰Amazon releases Chronos, a family of models for time series
Base model: amazon/chronos-t5-large
Paper: Chronos: Learning the Language of Time Series (2403.07815)
Models: https://huggingface.co/collections/amazon/chronos-models-65f1791d630a8d57cb718444

💡ORPO Alignment: align without a reference model nor SFT!
Paper: ORPO: Monolithic Preference Optimization without Reference Model (2403.07691)
Models: kaist-ai/orpo-65efef87544ba100aef30013
GitHub: https://github.com/xfactlab/orpo

🇺🇳Cohere releases 250M Wikipedia Embeddings in 300+ languages
Data: Cohere/wikipedia-2023-11-embed-multilingual-v3
Announcement: https://twitter.com/Nils_Reimers/status/1767891859207057618

🧬SegmentNT: a LLM for annotating DNA at single nucleotide resolution
Models: InstaDeepAI/segmentnt-65eb4941c57808b4a3fe1319
GitHub repo: https://github.com/instadeepai/nucleotide-transformer
Paper: https://www.biorxiv.org/content/10.1101/2024.03.14.584712v1

🚀DynamiCrafter: video generation models for interpolation and looping are out!
Project page: https://doubiiu.github.io/projects/DynamiCrafter/
GitHub: https://github.com/Doubiiu/DynamiCrafter
Demo: Doubiiu/DynamiCrafter_interp_loop

🚀Stanford releases Anticipatory Music Transformer:
GitHub: https://github.com/jthickstun/anticipation/
Models: https://hf.co/stanford-crfm
Original blog announcement: https://crfm.stanford.edu/2023/06/16/anticipatory-music-transformer.html

2 replies

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osanseviero

posted an update 9 months ago

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Diaries of Open Source. Part 8!

🤯CRM: Image-to-3D Textured Mesh
Demo: Zhengyi/CRM
Model: Zhengyi/CRM
Project page: https://ml.cs.tsinghua.edu.cn/~zhengyi/CRM/
Paper: CRM: Single Image to 3D Textured Mesh with Convolutional Reconstruction Model (2403.05034)

🤏Half Quadratic Quantization: super-fast quantization of very large models
Blog post: https://mobiusml.github.io/hqq_blog/
Colab: https://colab.research.google.com/drive/1cG_5R_u9q53Uond7F0JEdliwvoeeaXVN?usp=sharing
Repo: https://github.com/mobiusml/hqq

🤗GemMoE -Gemma + MoE
Model: Crystalcareai/GemMoE-Base-Random
Collection: Crystalcareai/gemmoe-65f11f4922af97ebe9943591

👀VeCLIP and MOFI, new 0-shot and image retrieval models by Apple, are now open-source!
GitHub: https://github.com/apple/ml-veclip/ and https://github.com/apple/ml-mofi
VeCLIP paper: From Scarcity to Efficiency: Improving CLIP Training via Visual-enriched Captions (2310.07699)
MOFI paper: MOFI: Learning Image Representations from Noisy Entity Annotated Images (2306.07952)

⚡SPIN: Recipe for alignment with very little data
Collection: argilla/dibt-prompt-collective-spin-65ef59062518776024395fc3
Tweetutorial: https://twitter.com/argilla_io/status/1767608154697699455

👀ViT Prisma - an interoperability library for vision models
GitHub: https://github.com/soniajoseph/ViT-Prisma

☕OpenLRM: full model and training code are open-sourced
Codebase: https://github.com/3DTopia/OpenLRM
Demo: zxhezexin/OpenLRM
Models: https://huggingface.co/zxhezexin

⚗️Oxford releases an extensive PEFT evaluation for bio models
Model: NTaylor/bio-mobilebert-mimic-mp-lora
GitHub: https://github.com/nlpie-research/efficient-ml
Paper: Efficiency at Scale: Investigating the Performance of Diminutive Language Models in Clinical Tasks (2402.10597)

🌍Data and models around the world
Hermes 2 Pro 7B: an upgraded Nous Hermes 2 model with strong function calling and JSON capabilities NousResearch/Hermes-2-Pro-Mistral-7B
Navarasa-2.0 : Gemma fine-tuned in 15 indian language Telugu-LLM-Labs/navarasa-65f5e6ffdf29f02c6d7767ce

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osanseviero

posted an update 9 months ago

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Diaries of Open Source. Part 7!

🔥Sakana releases Evolutionary Model Merge
Blog post: https://sakana.ai/evolutionary-model-merge/
Paper: Evolutionary Optimization of Model Merging Recipes (2403.13187)
Models and demo: https://hf.co/SakanaAI

🍞MixedBread releases new SoTA sentence embedding model
Announcement: https://www.mixedbread.ai/blog/mxbai-embed-large-v1
Model: mixedbread-ai/mxbai-embed-large-v1

🎥VideoMamba, a Mamba-based model for video understanding
Blog: https://hf.co/blog/vladbogo/video-mamba
Demo: OpenGVLab/VideoMamba
Model: OpenGVLab/VideoMamba

🔍 MathVerse, a visual math benchmark for multimodal LLMs
Paper page: https://mathverse-cuhk.github.io/
Dataset: AI4Math/MathVerse
Paper: MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems? (2403.14624)

🧠GraphWiz, a family of instruct-tuned LLMs to solve graph problems
Repos: https://hf.co/GraphWiz
Paper: GraphWiz: An Instruction-Following Language Model for Graph Problems (2402.16029)

🪆NLLB-SigLIP-MRL: a combination of NLLB and SigLIP trained with Matryoshka representation learning
Model: visheratin/nllb-siglip-mrl-large
Tweet: https://twitter.com/visheratin/status/1766643219909984734?s=46

🧍HDM and ProciGen: Template-free reconstruction of human-object interactions
Paper page: https://virtualhumans.mpi-inf.mpg.de/procigen-hdm/
Demo: xiexh20/HDM-interaction-recon
Models: xiexh20/HDM-models

🌎Models and data around the world
EagleX 7B, multi-lingual RNN-based model https://hf.co/spaces/recursal/EagleX-7B-1.7T-Gradio-Demo
Tamil LLM mervinpraison/tamil-large-language-model-7b-v1.0

2 replies

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osanseviero

posted an update 9 months ago

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1914

Diaries of Open Source. Part 6!

🏎️xAI releases Grok-1, a 314B MoE
Blog: https://x.ai/blog/grok-os
GH repo: https://github.com/xai-org/grok-1
Model: xai-org/grok-1

🕺MusicLang, a model for controllable music generation
Demo: musiclang/musiclang-predict
GH repo: https://github.com/musiclang/musiclang_predict

🔬BioT5: a family of models for biology and chemical text tasks
Base model: QizhiPei/biot5-base
Model for molecule captioning and design: QizhiPei/biot5-base-mol2text and QizhiPei/biot5-base-text2mol
GH Repo: https://github.com/QizhiPei/BioT5
Paper: BioT5: Enriching Cross-modal Integration in Biology with Chemical Knowledge and Natural Language Associations (2310.07276)

🤏Check out the AQLM and QMoE official weights from ISTA-DAS lab
Org: https://hf.co/ISTA-DASLab
Papers: Extreme Compression of Large Language Models via Additive Quantization (2401.06118) and QMoE: Practical Sub-1-Bit Compression of Trillion-Parameter Models (2310.16795)

🚀Community releases
Einstein-v4-7B, a Mistral fine-tune on high-quality data Weyaxi/Einstein-v4-7B
IL-7B, a Misttral fine-tune merge for rheumatology cmcmaster/il_7b
Caselaw Access Project, a collaboration to digitalize 40 million US court decisions from 6.7 million cases from 360 years https://hf.co/datasets/TeraflopAI/Caselaw_Access_Project

🌍Data and models around the world
HPLT Monolingual, a dataset of 75 languages with over 40TB of data HPLT/hplt_monolingual_v1_2
OpenLLM Turkish Benchmarks & Leaderboard malhajar/openllmturkishleadboard-datasets-65e5854490a87c0f2670ec18 and malhajar/OpenLLMTurkishLeaderboard
Occiglot, a collaborative effort for European LLMs with an initial release of 7B models for French, German, Spanish, and Italian occiglot/occiglot-eu5-7b-v01-65dbed502a6348b052695e01
Guftagoo, a Hindi+Hinglish multi-turn conversational dataset Tensoic/gooftagoo
AryaBhatta-Orca-Maths-Hindi dataset GenVRadmin/Aryabhatta-Orca-Maths-Hindi

1 reply

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osanseviero

posted an update 9 months ago

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Diaries of Open Source. Part 5!

🤯Contextual KTO Mistral PairRM: this model combines iterative KTO, SnorkelAI DPO dataset, Allenai PairRM for ranking, Mistral for the base model, and is a very strong model with Claude 3 quality on AlpacaEval 2.0
Final model: ContextualAI/Contextual_KTO_Mistral_PairRM
Dataset: snorkelai/Snorkel-Mistral-PairRM-DPO-Dataset
Leaderboard: https://tatsu-lab.github.io/alpaca_eval/
Base model: mistralai/Mistral-7B-Instruct-v0.2

🤏 tinyBenchmarks: Quick and cheap LLM evaluation!
Code: https://github.com/felipemaiapolo/tinyBenchmarks
Paper: tinyBenchmarks: evaluating LLMs with fewer examples (2402.14992)
Data: tinyBenchmarks/tinyMMLU

🎨Transformers.js 2.16 includes StableLM, speaker verification and diarization, and better chat templating. Try some fun demos!
- Xenova/video-object-detection
- Xenova/cross-encoder-web
- Xenova/the-tokenizer-playground

🏴‍☠️ Abascus Liberated-Qwen1.5-72B, a Qwen 72B-based model that strongly follows system prompts
Model: abacusai/Liberated-Qwen1.5-72B

👀Design2Code: benchmark of webpage screenshots to code
Data: SALT-NLP/Design2Code
Project https://salt-nlp.github.io/Design2Code/
Paper Design2Code: How Far Are We From Automating Front-End Engineering? (2403.03163)

🌎Data and models around the world
- One of the biggest Italian datasets https://hf.co/datasets/manalog/UsenetArchiveIT
- IndicLLMSuite: argest Pre-training and Instruction Fine-tuning dataset collection across 22 Indic languages ai4bharat/indicllmsuite-65ee7d225c337fcfa0991707
- Hebrew-Gemma-11B, the best base Hebrew model yam-peleg/Hebrew-Gemma-11B
- Komodo-7B, a family of multiple Indonesian languages LLMs Yellow-AI-NLP/komodo-7b-base

You can find the previous part at https://huggingface.co/posts/osanseviero/127895284909100

osanseviero

posted an update 10 months ago

Post

Diaries of Open Source. Part 4!

🌏Cohere and Cohere4AI release Command-R, a 35B model that is multilingual, RAG-optimized, and can manage tools!
Model: CohereForAI/c4ai-command-r-v01
Blog post: https://txt.cohere.com/command-r/

🧑‍🍳StarChat2: A powerful code model that is conversational
Try it out: HuggingFaceH4/starchat2-playground
Repos: HuggingFaceH4/starchat2-15b-65f068417b330fafad751fce
Training code: https://github.com/huggingface/alignment-handbook/tree/main/recipes/starchat2-15b

🐲Yi-9B: trained on 3 trillion tokens, this english-chinese LLM is quite good and with a very nice detailed report!
Model: 01-ai/Yi-9B
Paper: Yi: Open Foundation Models by 01.AI (2403.04652)

🐋DeepSeek-VL, 1.3B and 7B VLMs
Paper: DeepSeek-VL: Towards Real-World Vision-Language Understanding (2403.05525)
Large model: deepseek-ai/deepseek-vl-7b-chat

✍️Writer releases OmniACT: a dataset for multimodal agents for desktop and web.
Dataset: Writer/omniact
Paper: OmniACT: A Dataset and Benchmark for Enabling Multimodal Generalist Autonomous Agents for Desktop and Web (2402.17553)

🍎Apple releases MobileCLIP: fast image-text models! https://github.com/apple/ml-mobileclip

🦙💪LlamaGym - fine-tune LLM agents with RL in just a few lines of code! https://github.com/KhoomeiK/LlamaGym

🖼️New multimodal leaderboard ConTextual https://huggingface.co/blog/leaderboard-contextual

🎁 Design2Code: benchmark for multimodal LLMs for automating front-end development.
Dataset SALT-NLP/Design2Code
Paper Design2Code: How Far Are We From Automating Front-End Engineering? (2403.03163)
Project https://salt-nlp.github.io/Design2Code/

You can find the previous part at https://huggingface.co/posts/osanseviero/633758457910104

lewtun

posted an update 10 months ago

Post

Can we align code generation models to be good at chat without compromising their base capabilities 🤔?

This was the question the H4 team asked itself when BigCode released StarCoder2 a bit over a week ago. We knew that code models like deepseek-ai/deepseek-coder-6.7b-instruct and m-a-p/OpenCodeInterpreter-DS-33B get impressive scores on code benchmarks like HumanEval, but they tend to score poorly on chat benchmarks like MT Bench and IFEval. We also knew that the Zephyr recipe we applied to Mistral 7B produced a strong chat model, so we wondered -- could be tweaked to produce a strong coding assistant?

It turns out the answer is yes and I'm happy to share StarChat2, a DPO fine-tune of StarCoder2 15B that scores highly on both HumanEval and MT Bench / IFEval 🌟!

The most interesting lesson for me was that you get better models by blending in more code/math data than chat during the SFT step - in terms of tokens, we found a ratio of 3:1 worked best.

Anyway, here's a demo of the model, along with all the code and datasets we used to train it:

* Demo: HuggingFaceH4/starchat2-playground
* Collection: HuggingFaceH4/starchat2-15b-65f068417b330fafad751fce
* Recipe: https://github.com/huggingface/alignment-handbook

Hope it's useful to others!