From a366cc7245a3a933e9ecd984e1f082ba6fc41328 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Thu, 11 Jun 2026 06:00:17 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: EPFLiGHT/EuroLLM-9B-MeditronFO Source: Original Platform --- .gitattributes | 36 + README.md | 109 ++ chat_template.jinja | 4 + config.json | 29 + model-00001-of-00004.safetensors | 3 + model-00002-of-00004.safetensors | 3 + model-00003-of-00004.safetensors | 3 + model-00004-of-00004.safetensors | 3 + model.safetensors.index.json | 388 ++++++ special_tokens_map.json | 30 + tokenizer.json | 3 + tokenizer.model | 3 + tokenizer_config.json | 2108 ++++++++++++++++++++++++++++++ 13 files changed, 2722 insertions(+) create mode 100644 .gitattributes create mode 100644 README.md create mode 100644 chat_template.jinja create mode 100644 config.json create mode 100644 model-00001-of-00004.safetensors create mode 100644 model-00002-of-00004.safetensors create mode 100644 model-00003-of-00004.safetensors create mode 100644 model-00004-of-00004.safetensors create mode 100644 model.safetensors.index.json create mode 100644 special_tokens_map.json create mode 100644 tokenizer.json create mode 100644 tokenizer.model create mode 100644 tokenizer_config.json diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..52373fe --- /dev/null +++ b/.gitattributes @@ -0,0 +1,36 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text +tokenizer.json filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000..c848776 --- /dev/null +++ b/README.md @@ -0,0 +1,109 @@ +--- +license: apache-2.0 +language: +- en +library_name: transformers +pipeline_tag: text-generation +tags: +- medical +- clinical +- healthcare +- meditron +- fully-open +- medical-llm +base_model: utter-project/EuroLLM-9B-Instruct +base_model_relation: finetune +datasets: +- EPFLiGHT/fully-open-meditron +--- + +# EuroLLM-9B-MeditronFO + +**EuroLLM-9B-MeditronFO** is a 9B-parameter medical specialist LLM, produced by supervised fine-tuning of [EuroLLM-9B-Instruct](https://huggingface.co/utter-project/EuroLLM-9B-Instruct) on the [Fully Open Meditron Corpus](https://huggingface.co/datasets/EPFLiGHT/fully-open-meditron). + +This model is part of the **Fully Open Meditron** family — the first end-to-end auditable pipeline for clinical LLMs, with open weights, open data, open training recipe, and clinician-vetted corpus construction. + +> EuroLLM-9B-MeditronFO improves +11.43 points over its base on aggregate medical benchmarks. + +- 📄 **Paper:** [*Fully Open Meditron: An Auditable Pipeline for Clinical LLMs*](https://arxiv.org/abs/2605.16215) +- 💻 **Code:** [github.com/EPFLiGHT/FullyOpenMeditron](https://github.com/EPFLiGHT/FullyOpenMeditron) +- 📚 **Collection:** [MeditronFO](https://huggingface.co/collections/EPFLiGHT/meditronfo) +- 🗂️ **Training corpus:** [EPFLiGHT/fully-open-meditron](https://huggingface.co/datasets/EPFLiGHT/fully-open-meditron) + +## Performance + +Accuracy (%) on standard medical benchmarks. See the paper for full evaluation details, confidence intervals, and open-ended Auto-MOOVE results. + +| Benchmark | EuroLLM-9B-Instruct | **EuroLLM-9B-MeditronFO** | Δ | +|---|---:|---:|---:| +| MedMCQA | 37.84 | **46.98** | +9.14 | +| MedQA | 48.55 | **49.73** | +1.18 | +| PubMedQA | 40.00 | **67.40** | +27.40 | +| MedXpertQA | 10.33 | **11.63** | +1.30 | +| HealthBench Hard | 13.47 | **31.62** | +18.15 | +| **Average** | 30.04 | **41.47** | +11.43 | + +## Usage + +```python +from transformers import AutoModelForCausalLM, AutoTokenizer +import torch + +model_id = "EPFLiGHT/EuroLLM-9B-MeditronFO" +tokenizer = AutoTokenizer.from_pretrained(model_id) +model = AutoModelForCausalLM.from_pretrained( + model_id, + torch_dtype=torch.bfloat16, + device_map="auto", +) + +messages = [ + {"role": "user", "content": "A 62-year-old woman presents with a three-day history of dyspnea on exertion and a productive cough. What is the differential diagnosis?"}, +] +inputs = tokenizer.apply_chat_template( + messages, + add_generation_prompt=True, + tokenize=True, + return_dict=True, + return_tensors="pt", +).to(model.device) + +outputs = model.generate(**inputs, max_new_tokens=512, do_sample=False) +print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:], skip_special_tokens=True)) +``` + +## Training + +- **Base model:** [EuroLLM-9B-Instruct](https://huggingface.co/utter-project/EuroLLM-9B-Instruct) +- **Corpus:** [Fully Open Meditron](https://huggingface.co/datasets/EPFLiGHT/fully-open-meditron) — ~601k examples (~150M tokens), aggregating eight public medical QA datasets with three clinician-vetted synthetic components: exam-style QA, guideline-grounded QA from 46,469 clinical practice guidelines, and open-ended clinical vignettes +- **Hardware:** NVIDIA GH200 nodes +- **Framework:** Axolotl with FSDP v2 / DeepSpeed ZeRO-3, Flash Attention 2, bf16 mixed precision +- **Decontamination:** System-wide two-stage n-gram and token-alignment decontamination against all evaluation benchmarks + +Full hyperparameters are in Appendix I of the paper. + +## Intended Use + +**Research only.** This model is intended to support research on medical LLMs, auditing of clinical AI systems, and reproducibility of the Fully Open Meditron pipeline. + +It is **not validated for clinical deployment, individual patient advice, autonomous decision-making, or any other deployment-adjacent use.** Conduct independent domain-specific safety evaluation before any such use. + +## Citation + +If you use this model, please cite: + +```bibtex +@misc{theimerlienhard2026fullyopenmeditronauditable, + title = {Fully Open Meditron: An Auditable Pipeline for Clinical LLMs}, + author = {Xavier Theimer-Lienhard and Mushtaha El-Amin and Fay Elhassan and Sahaj Vaidya and Victor Cartier-Negadi and David Sasu and Lars Klein and Mary-Anne Hartley}, + year = {2026}, + eprint = {2605.16215}, + archivePrefix = {arXiv}, + primaryClass = {cs.AI}, + url = {https://arxiv.org/abs/2605.16215} +} +``` + +## License + +Released under the **apache-2.0** license. 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