Instructions to use StephenRGS/Doctorian-MedCore with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StephenRGS/Doctorian-MedCore with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("StephenRGS/Doctorian-MedCore", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,225 Bytes
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license: apache-2.0
datasets:
- Zowel/medical_imaging_diagnostic_reports
- nezahatkorkmaz/Turkish-medical-visual-question-answering-LLaVa-dataset
- Cath1y/embodied-ai-literature-metadata
- fineset-io/vision-language-action-papers
- LangAGI-Lab/magpie-reasoning-v1-10k-step-by-step-rationale
- Vyber07/cyber-security
- AlicanKiraz0/Cybersecurity-Dataset-Fenrir-v2.1
- ankitjh4/bharat-government-documents
- openai/gsm8k
- MaziyarPanahi/Jev-RAG-Claim-Verification-130K
- MoreThought/Fable-5.1-Max-Reasoning-Filtered-10000x
- scenario-labs/3d-collection
- nisten/opus5-5-doctor-patient-conversations-all-human-diseases
- LocalLLaMA/typed-decisions
- bakrianoo/jabarti-llm-dataset
- HuggingFaceFW/fineweb-edu
- LightwheelAI/EgoStandard
- Necent/llm-jailbreak-prompt-injection-dataset
- CohereLabs/10-2026-qwen-investigation-traces
- harvardMadsys/freeinference_agentic_trace
language:
- en
- sw
- af
- fr
- zh
- es
- ko
- la
- gd
- el
- ig
metrics:
- Vickyage/accents_unplugged_eval
- accuracy
- google_bleu
- responsible-ai-labs/rail_score
base_model:
- google/gemma-4-31B-it
- mistralai/Mistral-Large-4-1T-A52B
new_version: mistralai/Mistral-Large-4-1T-A52B
library_name: transformers
tags:
- Doctorian
- medical
- Core
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