Standardized benchmark and leaderboard for Clinical Named Entity Recognition
AI & ML interests
None defined yet.
Recent Activity
View all activity
Organization Card
M42 Health
Welcome to the official Hugging Face organization for foundation models by M42 Health. M42 is a global, tech-enabled healthcare company based in Abu Dhabi, UAE.
Model Index
| Model | Size | Description | Link |
|---|---|---|---|
| CXformer | 22M/87M | Chest X-Ray foundation models trained with efficient traning framework | small, base |
| BioFM-265M | 265M | Biologically informed genomic foundation model | link |
| Med42-v2-70B | 70B | Instruction-tuned and clinically aligned model to suit healthcare preferences | link |
| Med42-v2-8B | 8B | Instruction-tuned and clinically aligned model to suit healthcare preferences | link |
| Med42-70B | 70B | Instruction-tuned on open datasets including medical flashcards, medical questions, and open-domain dialogues | link |
Copyright 2025 M42.
SoTA clinical LLMs and the techniques to build them.
-
Beyond Fine-tuning: Unleashing the Potential of Continuous Pretraining for Clinical LLMs
Paper β’ 2409.14988 β’ Published β’ 23 -
Med42-v2: A Suite of Clinical LLMs
Paper β’ 2408.06142 β’ Published β’ 52 -
Med42 -- Evaluating Fine-Tuning Strategies for Medical LLMs: Full-Parameter vs. Parameter-Efficient Approaches
Paper β’ 2404.14779 β’ Published β’ 1 -
m42-health/Llama3-Med42-70B
Text Generation β’ 71B β’ Updated β’ 2.56k β’ β’ 64
Standardized benchmark and leaderboard for Clinical Named Entity Recognition
SoTA clinical LLMs and the techniques to build them.
-
Beyond Fine-tuning: Unleashing the Potential of Continuous Pretraining for Clinical LLMs
Paper β’ 2409.14988 β’ Published β’ 23 -
Med42-v2: A Suite of Clinical LLMs
Paper β’ 2408.06142 β’ Published β’ 52 -
Med42 -- Evaluating Fine-Tuning Strategies for Medical LLMs: Full-Parameter vs. Parameter-Efficient Approaches
Paper β’ 2404.14779 β’ Published β’ 1 -
m42-health/Llama3-Med42-70B
Text Generation β’ 71B β’ Updated β’ 2.56k β’ β’ 64
models
7
m42-health/gfm-mistral-base-500m
Updated
β’
8
m42-health/CXformer-small
Image Feature Extraction
β’
22.1M
β’
Updated
β’
3
β’
2
m42-health/CXformer-base
Image Feature Extraction
β’
86.6M
β’
Updated
β’
35
β’
1
m42-health/BioFM-265M
0.3B
β’
Updated
β’
8
β’
11
m42-health/Llama3-Med42-8B
Text Generation
β’
8B
β’
Updated
β’
2.14k
β’
β’
74
m42-health/Llama3-Med42-70B
Text Generation
β’
71B
β’
Updated
β’
2.56k
β’
β’
64
m42-health/med42-70b
Text Generation
β’
Updated
β’
10
β’
184
datasets
5
m42-health/HC4
Viewer
β’
Updated
β’
9.77M
β’
387
β’
4
m42-health/variant-benchmark
Viewer
β’
Updated
β’
1.88M
β’
42
β’
2
m42-health/ancestry_dataset
Viewer
β’
Updated
β’
70.4k
β’
10
m42-health/biotypes
Viewer
β’
Updated
β’
19.6k
β’
7
β’
1
m42-health/tp53
Viewer
β’
Updated
β’
1.23k
β’
9