Training mRNA Language Models Across 25 Species for $165
โข 28
AI & ML interests
healthcare AI, clinical NER, biomedical NLP, PII / de-identification, on-device AI, edge inference, Apple Silicon / MLX, data sovereignty, privacy-preserving ML, open-source
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MaziyarPanahiย
updated a
Space 7 days ago
MaziyarPanahiย
updated a
Space 17 days ago
MaziyarPanahiย
posted an update 5 months ago
Post
5464
Training mRNA Language Models Across 25 Species for $165
We built an end-to-end protein AI pipeline covering structure prediction, sequence design, and codon optimization. After comparing multiple transformer architectures for codon-level language modeling, CodonRoBERTa-large-v2 emerged as the clear winner with a perplexity of 4.10 and a Spearman CAI correlation of 0.40, significantly outperforming ModernBERT. We then scaled to 25 species, trained 4 production models in 55 GPU-hours, and built a species-conditioned system that no other open-source project offers. Complete results, architectural decisions, and runnable code below.
https://huggingface.co/blog/OpenMed/training-mrna-models-25-species
We built an end-to-end protein AI pipeline covering structure prediction, sequence design, and codon optimization. After comparing multiple transformer architectures for codon-level language modeling, CodonRoBERTa-large-v2 emerged as the clear winner with a perplexity of 4.10 and a Spearman CAI correlation of 0.40, significantly outperforming ModernBERT. We then scaled to 25 species, trained 4 production models in 55 GPU-hours, and built a species-conditioned system that no other open-source project offers. Complete results, architectural decisions, and runnable code below.
https://huggingface.co/blog/OpenMed/training-mrna-models-25-species
- 1 reply
MaziyarPanahiย
posted an update 5 months ago
Post
2444
We annotated 119K medical images with two frontier VLMs (Qwen 3.5, Kimi K2.5), cross-validated at 93% agreement, and produced 110K training records, all for under $500. Fine-tuning 3 small models (2-3B params) improved all benchmarks: best model reaches +15.0% average exact match.
Everything is open-sourced: datasets, adapters, and code.
https://huggingface.co/blog/OpenMed/synthvision
Everything is open-sourced: datasets, adapters, and code.
https://huggingface.co/blog/OpenMed/synthvision
- 2 replies
MaziyarPanahiย
posted an update 6 months ago
Post
5007
DNA, mRNA, proteins, AI. I spent the last year going deep into computational biology as an ML engineer. This is Part I of what I found. ๐งฌ
In 2024, AlphaFold won the Nobel Prize in Chemistry.
By 2026, the open-source community had built alternatives that outperform it.
That's the story I find most interesting about protein AI right now. Not just the science (which is incredible), but the speed at which open-source caught up. Multiple teams, independently, reproduced and then exceeded AlphaFold 3's accuracy with permissive licenses. The field went from prediction to generation: we're not just modeling known proteins anymore, we're designing new ones.
I spent months mapping this landscape for ML engineers. What the architectures actually are (spoiler: transformers and diffusion models), which tools to use for what, and which ones you can actually ship commercially.
New post on the Hugging Face blog: https://huggingface.co/blog/MaziyarPanahi/protein-ai-landscape
Hope you all enjoy! ๐ค
In 2024, AlphaFold won the Nobel Prize in Chemistry.
By 2026, the open-source community had built alternatives that outperform it.
That's the story I find most interesting about protein AI right now. Not just the science (which is incredible), but the speed at which open-source caught up. Multiple teams, independently, reproduced and then exceeded AlphaFold 3's accuracy with permissive licenses. The field went from prediction to generation: we're not just modeling known proteins anymore, we're designing new ones.
I spent months mapping this landscape for ML engineers. What the architectures actually are (spoiler: transformers and diffusion models), which tools to use for what, and which ones you can actually ship commercially.
New post on the Hugging Face blog: https://huggingface.co/blog/MaziyarPanahi/protein-ai-landscape
Hope you all enjoy! ๐ค
- 2 replies
MaziyarPanahiย
authored a
paper 6 months ago
MaziyarPanahiย
posted an update 7 months ago
Post
2600
Announcing: OpenMed Multilingual PII Detection Models
Today I am releasing 105 open-source models for Personally Identifiable Information (PII) detection in French, German, and Italian.
All Apache 2.0 licensed. Free for commercial use. No restrictions.
Performance:
- French: 97.97% F1 (top model)
- German: 97.61% F1 (top model)
- Italian: 97.28% F1 (top model)
All top-10 models per language exceed 96% F1
Coverage:
55+ PII entity types per language
Native ID formats: NSS (French), Sozialversicherungsnummer (German), Codice Fiscale (Italian)
Language-specific address, phone, and name patterns
Training Data:
French: 49,580 samples
German: 42,250 samples
Italian: 40,944 samples
Why Multilingual?
European healthcare operates in European languages. Clinical notes, patient records, and medical documents are generated in French, German, Italian, and other languages.
Effective de-identification requires:
- Native language understanding โ not translation
- Local ID format recognition โ each country has unique patterns
- Cultural context awareness โ names, addresses, and formats vary
- These models deliver production-ready accuracy without requiring data to leave your infrastructure or language.
HIPAA & GDPR Compliance
Built for US and European privacy regulations:
- On-premise deployment: Process data locally with zero external dependencies
- Data sovereignty: No API calls, no cloud services, no cross-border transfers
- Air-gapped capable: Deploy in fully isolated environments if required
- Regulatory-grade accuracy: Supporting Expert Determination standards
- HIPAA and GDPR compliance across languages, without compliance gaps.
Use Cases
- Hospital EHR systems: Automated patient record de-identification
- Clinical research: Multilingual dataset preparation for studies
- Insurance companies: Claims processing across
https://huggingface.co/collections/OpenMed/multilingual-pii-and-de-identification
Today I am releasing 105 open-source models for Personally Identifiable Information (PII) detection in French, German, and Italian.
All Apache 2.0 licensed. Free for commercial use. No restrictions.
Performance:
- French: 97.97% F1 (top model)
- German: 97.61% F1 (top model)
- Italian: 97.28% F1 (top model)
All top-10 models per language exceed 96% F1
Coverage:
55+ PII entity types per language
Native ID formats: NSS (French), Sozialversicherungsnummer (German), Codice Fiscale (Italian)
Language-specific address, phone, and name patterns
Training Data:
French: 49,580 samples
German: 42,250 samples
Italian: 40,944 samples
Why Multilingual?
European healthcare operates in European languages. Clinical notes, patient records, and medical documents are generated in French, German, Italian, and other languages.
Effective de-identification requires:
- Native language understanding โ not translation
- Local ID format recognition โ each country has unique patterns
- Cultural context awareness โ names, addresses, and formats vary
- These models deliver production-ready accuracy without requiring data to leave your infrastructure or language.
HIPAA & GDPR Compliance
Built for US and European privacy regulations:
- On-premise deployment: Process data locally with zero external dependencies
- Data sovereignty: No API calls, no cloud services, no cross-border transfers
- Air-gapped capable: Deploy in fully isolated environments if required
- Regulatory-grade accuracy: Supporting Expert Determination standards
- HIPAA and GDPR compliance across languages, without compliance gaps.
Use Cases
- Hospital EHR systems: Automated patient record de-identification
- Clinical research: Multilingual dataset preparation for studies
- Insurance companies: Claims processing across
https://huggingface.co/collections/OpenMed/multilingual-pii-and-de-identification
- 1 reply
MaziyarPanahiย
posted an update 7 months ago
Post
1411
From Golden Gate Bridge to Broken JSON: Why Anthropic's SAE Steering Fails for Structured Output
I ran 6 experiments trying to use Anthropic's SAE steering for JSON generation.
- Base model: 86.8% valid JSON
- Steering only: 24.4%
- Fine-tuned: 96.6%
- FSM constrained: 100%
Steering is for semantics, not syntax.
https://huggingface.co/blog/MaziyarPanahi/sae-steering-json
I ran 6 experiments trying to use Anthropic's SAE steering for JSON generation.
- Base model: 86.8% valid JSON
- Steering only: 24.4%
- Fine-tuned: 96.6%
- FSM constrained: 100%
Steering is for semantics, not syntax.
https://huggingface.co/blog/MaziyarPanahi/sae-steering-json
MaziyarPanahiย
posted an update 7 months ago
Post
4162
๐จ Day 8/8: OpenMed Medical Reasoning Dataset Release - THE GRAND FINALE
Today I complete my 8-day release series with Medical-Reasoning-SFT-Mega.
The largest open medical reasoning dataset, combining 7 state-of-the-art AI models with fair distribution deduplication.
THE 7 SOURCE MODELS (Original Sample Counts):
1. Trinity-Mini: 810,284 samples
2. Qwen3-Next-80B: 604,249 samples
3. GPT-OSS-120B: 506,150 samples
4. Nemotron-Nano-30B: 444,544 samples
5. GLM-4.5-Air: 225,179 samples
6. MiniMax-M2.1: 204,773 samples
7. Baichuan-M3-235B: 124,520 samples
TOTAL BEFORE DEDUPLICATION: 2,919,699 samples
TOKEN COUNTS:
- Content tokens: 2.22 Billion
- Reasoning tokens: 1.56 Billion
- Total tokens: 3.78 Billion
- Samples with chain-of-thought: 100%
Quick Start:
All datasets Apache 2.0 licensed. Free for research and commercial use.
Thank you for following OpenMed's release series. I can't wait to see what you build. ๐ฅ
OpenMed/Medical-Reasoning-SFT-Mega
OpenMed/Medical-Reasoning-SFT-GPT-OSS-120B-V2
OpenMed/Medical-Reasoning-SFT-Trinity-Mini
OpenMed/Medical-Reasoning-SFT-GLM_4.5_Air
OpenMed/Medical-Reasoning-SFT-MiniMax-M2.1
OpenMed/Medical-Reasoning-SFT-Qwen3-Next-80B
OpenMed/Medical-Reasoning-SFT-Nemotron-Nano-30B
OpenMed/Medical-Reasoning-SFT-Baichuan-M3-235B
https://huggingface.co/collections/OpenMed/medical-datasets
Today I complete my 8-day release series with Medical-Reasoning-SFT-Mega.
The largest open medical reasoning dataset, combining 7 state-of-the-art AI models with fair distribution deduplication.
THE 7 SOURCE MODELS (Original Sample Counts):
1. Trinity-Mini: 810,284 samples
2. Qwen3-Next-80B: 604,249 samples
3. GPT-OSS-120B: 506,150 samples
4. Nemotron-Nano-30B: 444,544 samples
5. GLM-4.5-Air: 225,179 samples
6. MiniMax-M2.1: 204,773 samples
7. Baichuan-M3-235B: 124,520 samples
TOTAL BEFORE DEDUPLICATION: 2,919,699 samples
TOKEN COUNTS:
- Content tokens: 2.22 Billion
- Reasoning tokens: 1.56 Billion
- Total tokens: 3.78 Billion
- Samples with chain-of-thought: 100%
Quick Start:
from datasets import load_dataset
ds = load_dataset("OpenMed/Medical-Reasoning-SFT-Mega")All datasets Apache 2.0 licensed. Free for research and commercial use.
Thank you for following OpenMed's release series. I can't wait to see what you build. ๐ฅ
OpenMed/Medical-Reasoning-SFT-Mega
OpenMed/Medical-Reasoning-SFT-GPT-OSS-120B-V2
OpenMed/Medical-Reasoning-SFT-Trinity-Mini
OpenMed/Medical-Reasoning-SFT-GLM_4.5_Air
OpenMed/Medical-Reasoning-SFT-MiniMax-M2.1
OpenMed/Medical-Reasoning-SFT-Qwen3-Next-80B
OpenMed/Medical-Reasoning-SFT-Nemotron-Nano-30B
OpenMed/Medical-Reasoning-SFT-Baichuan-M3-235B
https://huggingface.co/collections/OpenMed/medical-datasets
- 6 replies
MaziyarPanahiย
posted an update 8 months ago
Post
3843
๐ OpenMed 2025 Year in Review: 6 Months of Open Medical AI
I'm thrilled to share what the OpenMed community has accomplished since our July 2025 launch!
๐ The Numbers
29,700,000 downloads Thank you! ๐
- 481 total models (475 medical NER models + 6 fine-tuned LLMs)
- 475 medical NER models in [OpenMed](
OpenMed ) organization
- 6 fine-tuned LLMs in [openmed-community](
openmed-community )
- 551,800 PyPI downloads of the [openmed package](https://pypi.org/project/openmed/)
- 707 followers on HuggingFace (you!)
- 97 GitHub stars on the [toolkit repo](https://github.com/maziyarpanahi/openmed)
๐ Top Models by Downloads
1. [OpenMed-NER-PharmaDetect-SuperClinical-434M]( OpenMed/OpenMed-NER-PharmaDetect-SuperClinical-434M) โ 147,305 downloads
2. [OpenMed-NER-ChemicalDetect-ElectraMed-33M]( OpenMed/OpenMed-NER-ChemicalDetect-ElectraMed-33M) โ 126,785 downloads
3. [OpenMed-NER-BloodCancerDetect-TinyMed-65M]( OpenMed/OpenMed-NER-BloodCancerDetect-TinyMed-65M) โ 126,465 downloads
๐ฌ Model Categories
Our 481 models cover comprehensive medical domains:
- Disease Detection (~50 variants)
- Pharmaceutical Detection (~50 variants)
- Oncology Detection (~50 variants)
- Genomics/DNA Detection (~80 variants)
- Chemical Detection (~50 variants)
- Species/Organism Detection (~60 variants)
- Protein Detection (~50 variants)
- Pathology Detection (~50 variants)
- Blood Cancer Detection (~30 variants)
- Anatomy Detection (~40 variants)
- Zero-Shot NER (GLiNER-based)
OpenMed
OpenMed NER: Open-Source, Domain-Adapted State-of-the-Art Transformers for Biomedical NER Across 12 Public Datasets (2508.01630)
https://huggingface.co/collections/OpenMed/medical-and-clinical-ner
https://huggingface.co/collections/OpenMed/zeroshot-medical-and-clinical-ner
OpenMed/Medical-Reasoning-SFT-GPT-OSS-120B
I'm thrilled to share what the OpenMed community has accomplished since our July 2025 launch!
๐ The Numbers
29,700,000 downloads Thank you! ๐
- 481 total models (475 medical NER models + 6 fine-tuned LLMs)
- 475 medical NER models in [OpenMed](
- 6 fine-tuned LLMs in [openmed-community](
- 551,800 PyPI downloads of the [openmed package](https://pypi.org/project/openmed/)
- 707 followers on HuggingFace (you!)
- 97 GitHub stars on the [toolkit repo](https://github.com/maziyarpanahi/openmed)
๐ Top Models by Downloads
1. [OpenMed-NER-PharmaDetect-SuperClinical-434M]( OpenMed/OpenMed-NER-PharmaDetect-SuperClinical-434M) โ 147,305 downloads
2. [OpenMed-NER-ChemicalDetect-ElectraMed-33M]( OpenMed/OpenMed-NER-ChemicalDetect-ElectraMed-33M) โ 126,785 downloads
3. [OpenMed-NER-BloodCancerDetect-TinyMed-65M]( OpenMed/OpenMed-NER-BloodCancerDetect-TinyMed-65M) โ 126,465 downloads
๐ฌ Model Categories
Our 481 models cover comprehensive medical domains:
- Disease Detection (~50 variants)
- Pharmaceutical Detection (~50 variants)
- Oncology Detection (~50 variants)
- Genomics/DNA Detection (~80 variants)
- Chemical Detection (~50 variants)
- Species/Organism Detection (~60 variants)
- Protein Detection (~50 variants)
- Pathology Detection (~50 variants)
- Blood Cancer Detection (~30 variants)
- Anatomy Detection (~40 variants)
- Zero-Shot NER (GLiNER-based)
OpenMed NER: Open-Source, Domain-Adapted State-of-the-Art Transformers for Biomedical NER Across 12 Public Datasets (2508.01630)
https://huggingface.co/collections/OpenMed/medical-and-clinical-ner
https://huggingface.co/collections/OpenMed/zeroshot-medical-and-clinical-ner
OpenMed/Medical-Reasoning-SFT-GPT-OSS-120B
- 1 reply
Post
14763
deepseek-ai/DeepSeek-OCR is out! ๐ฅ my take โคต๏ธ
> pretty insane it can parse and re-render charts in HTML
> it uses CLIP and SAM features concatenated, so better grounding
> very efficient per vision tokens/performance ratio
> covers 100 languages
> pretty insane it can parse and re-render charts in HTML
> it uses CLIP and SAM features concatenated, so better grounding
> very efficient per vision tokens/performance ratio
> covers 100 languages
- 5 replies
Post
7104
large AI labs open-sourced a ton of models last week ๐ฅ
here's few picks, find even more here merve/sep-16-releases-68d13ea4c547f02f95842f05 ๐ค
> IBM released a new Docling model with 258M params based on Granite (A2.0) ๐ ibm-granite/granite-docling-258M
> Xiaomi released 7B audio LM with base and instruct variants (MIT) XiaomiMiMo/mimo-audio-68cc7202692c27dae881cce0
> DecartAI released Lucy Edit, open Nano Banana ๐ (NC) decart-ai/Lucy-Edit-Dev
> OpenGVLab released a family of agentic computer use models (3B/7B/32B) with the dataset ๐ป OpenGVLab/scalecua-68c912cf56f7ff4c8e034003
> Meituan Longcat released thinking version of LongCat-Flash ๐ญ meituan-longcat/LongCat-Flash-Thinking
here's few picks, find even more here merve/sep-16-releases-68d13ea4c547f02f95842f05 ๐ค
> IBM released a new Docling model with 258M params based on Granite (A2.0) ๐ ibm-granite/granite-docling-258M
> Xiaomi released 7B audio LM with base and instruct variants (MIT) XiaomiMiMo/mimo-audio-68cc7202692c27dae881cce0
> DecartAI released Lucy Edit, open Nano Banana ๐ (NC) decart-ai/Lucy-Edit-Dev
> OpenGVLab released a family of agentic computer use models (3B/7B/32B) with the dataset ๐ป OpenGVLab/scalecua-68c912cf56f7ff4c8e034003
> Meituan Longcat released thinking version of LongCat-Flash ๐ญ meituan-longcat/LongCat-Flash-Thinking
- 2 replies
Post
3602
IBM just released small swiss army knife for the document models: granite-docling-258M on Hugging Face ๐ฅ
> not only a document converter but also can do document question answering, understand multiple languages ๐คฏ
> best part: released with Apache 2.0 license ๐ use it with your commercial projects!
> it supports transformers, vLLM and MLX from the get-go! ๐ค
> built on SigLIP2 & granite-165M
model: ibm-granite/granite-docling-258M
demo: ibm-granite/granite-docling-258m-demo ๐
> not only a document converter but also can do document question answering, understand multiple languages ๐คฏ
> best part: released with Apache 2.0 license ๐ use it with your commercial projects!
> it supports transformers, vLLM and MLX from the get-go! ๐ค
> built on SigLIP2 & granite-165M
model: ibm-granite/granite-docling-258M
demo: ibm-granite/granite-docling-258m-demo ๐
Post
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a ton of image/video generation models and LLMs from big labs ๐ฅ
> Meta released facebook/mobilellm-r1-68c4597b104fac45f28f448e, smol LLMs for on-device use ๐ฌ
> Tencent released tencent/SRPO, high res image generation model and tencent/POINTS-Reader, cutting edge OCR ๐
> ByteDance released bytedance-research/HuMo, video generation from any input โฏ๏ธ
find more models, datasets, demos here merve/sep-11-releases-68c7dbfa26bea8cd921fa0ac
> Meta released facebook/mobilellm-r1-68c4597b104fac45f28f448e, smol LLMs for on-device use ๐ฌ
> Tencent released tencent/SRPO, high res image generation model and tencent/POINTS-Reader, cutting edge OCR ๐
> ByteDance released bytedance-research/HuMo, video generation from any input โฏ๏ธ
find more models, datasets, demos here merve/sep-11-releases-68c7dbfa26bea8cd921fa0ac
Post
1112
fan-favorite vision LM Florence-2 is now officially supported in transformers ๐ค
find all the models in
florence-community org ๐ซก
find all the models in
Post
1899
past week was great for open LLMs ๐ฅ merve/sep-1-releases-68bede0e729c12597eefd050
> Google released google/embeddinggemma-300m, new embedding model with 300M params
> new update to Kimi-K2 just landed moonshotai/Kimi-K2-Instruct-0905 ๐
> OpenBMB released a new version to MiniCPM with 8B params openbmb/MiniCPM4.1-8B
also soooo many Qwen-Image & Kontext LoRAs dropped!
> Google released google/embeddinggemma-300m, new embedding model with 300M params
> new update to Kimi-K2 just landed moonshotai/Kimi-K2-Instruct-0905 ๐
> OpenBMB released a new version to MiniCPM with 8B params openbmb/MiniCPM4.1-8B
also soooo many Qwen-Image & Kontext LoRAs dropped!
Post
3792
upgrade your transformers ๐ฅ
it comes with insanely capable models like merve/sam2-66ac9deac6fca3bc5482fe30, microsoft/kosmos-2.5, and more ๐ซก
I built a notebook you can run with free Colab T4 to walk through the API for new models ๐๐ปโโ๏ธ merve/smol-vision
fine-tuning will follow-up soon!
it comes with insanely capable models like merve/sam2-66ac9deac6fca3bc5482fe30, microsoft/kosmos-2.5, and more ๐ซก
I built a notebook you can run with free Colab T4 to walk through the API for new models ๐๐ปโโ๏ธ merve/smol-vision
fine-tuning will follow-up soon!
Post
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large AI labs have dropped so many open models last week ๐ฅ don't miss out on them
โ Apple released on-device vision LMs apple/fastvlm-68ac97b9cd5cacefdd04872e & apple/mobileclip2-68ac947dcb035c54bcd20c47
โ OpenGVLab released InternVL3.5, 32 new vision LMs with one based on gpt-oss! (OS) OpenGVLab/internvl35-68ac87bd52ebe953485927fb
โ MSFT released a killer small TTS model (OS) microsoft/VibeVoice-1.5B
find more herehttps://huggingface.co/collections/merve/august-29-releases-68b5a3754cfb8abf59e2b486
โ Apple released on-device vision LMs apple/fastvlm-68ac97b9cd5cacefdd04872e & apple/mobileclip2-68ac947dcb035c54bcd20c47
โ OpenGVLab released InternVL3.5, 32 new vision LMs with one based on gpt-oss! (OS) OpenGVLab/internvl35-68ac87bd52ebe953485927fb
โ MSFT released a killer small TTS model (OS) microsoft/VibeVoice-1.5B
find more herehttps://huggingface.co/collections/merve/august-29-releases-68b5a3754cfb8abf59e2b486
- 1 reply
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first vision language model built off openai/gpt-oss-20b just dropped! ๐ฅ
InternVL3.5 comes with 32 models ๐คฏ pre-trained, fine-tuned, aligned in various sizes OpenGVLab/internvl35-68ac87bd52ebe953485927fb
comes with gpt-oss or Qwen3 for LLM part โคต๏ธ
InternVL3.5 comes with 32 models ๐คฏ pre-trained, fine-tuned, aligned in various sizes OpenGVLab/internvl35-68ac87bd52ebe953485927fb
comes with gpt-oss or Qwen3 for LLM part โคต๏ธ
- 1 reply
Post
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GPT-4.1-mini level model right in your iPhone ๐คฏ
openbmb/MiniCPM-V-4 is only 4B while surpassing GPT-4.1-mini in vision benchmarks ๐ฅ
allows commercial use as well!
openbmb/MiniCPM-V-4 is only 4B while surpassing GPT-4.1-mini in vision benchmarks ๐ฅ
allows commercial use as well!