From 26e7b1e5e0e2b242fb2640921693c88f5f593ad9 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Sun, 18 Oct 2026 23:34:21 +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: BEncoderRT/medical_inference Source: Original Platform --- .gitattributes | 36 ++++++++++++++++ README.md | 108 ++++++++++++++++++++++++++++++++++++++++++++++ config.json | 3 ++ unsloth.Q8_0.gguf | 3 ++ 4 files changed, 150 insertions(+) create mode 100644 .gitattributes create mode 100644 README.md create mode 100644 config.json create mode 100644 unsloth.Q8_0.gguf diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..5535775 --- /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 +unsloth.Q8_0.gguf filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000..f78e149 --- /dev/null +++ b/README.md @@ -0,0 +1,108 @@ +--- +license: apache-2.0 +datasets: +- FreedomIntelligence/medical-o1-reasoning-SFT +language: +- zh +base_model: +- unsloth/DeepSeek-R1-Distill-Llama-8B +pipeline_tag: text-generation +tags: +- unsloth +- deepseek +- rola +- sft +--- + +# DeepSeek-R1 Medical Reasoning Model + +This repository contains a **fine-tuned medical reasoning model** based on +[DeepSeek-R1-Distill-Llama-8B](https://huggingface.co/unsloth/DeepSeek-R1-Distill-Llama-8B) +and trained on the [medical-o1-reasoning-SFT](https://huggingface.co/datasets/FreedomIntelligence/medical-o1-reasoning-SFT) dataset. + +⚠️ **The uploaded file (`unsloth.Q8_0.gguf`) contains quantized weights** for efficient inference. + +--- + +## 🔍 Model Overview + +- **Base Model**: unsloth/DeepSeek-R1-Distill-Llama-8B +- **Training Method**: SFT (Supervised Fine-Tuning) +- **Domain**: Medical reasoning and clinical knowledge +- **Language**: English +- **Quantization**: Q8_0 (gguf format for efficient inference) + +--- + +## 📚 Training Data + +The model was fine-tuned on: + +- **Dataset**: `FreedomIntelligence/medical-o1-reasoning-SFT` +- **Language**: English +- **Task**: Medical reasoning, clinical question-answering + +--- + +## 🚀 Usage Example + +> **Note:** The model is stored in `.gguf` format (quantized). You can load it using `unsloth` library. + +```python +from unsloth import FastLanguageModel +import torch + +# Load the quantized GGUF model +model, tokenizer = FastLanguageModel.from_pretrained( + "./unsloth.Q8_0.gguf", + max_seq_length=2048, + load_in_8bit=True, # optional depending on quantization +) + +FastLanguageModel.for_inference(model) + +def generate(model, prompt, max_new_tokens=200): + inputs = tokenizer(prompt, return_tensors="pt").to("cuda") + + with torch.no_grad(): + outputs = model.generate( + **inputs, + max_new_tokens=max_new_tokens, + do_sample=True, + temperature=0.7, + top_p=0.9, + ) + + return tokenizer.decode(outputs[0], skip_special_tokens=True) + +# Example prompt +prompt = """### Instruction: +"一个患有急性阑尾炎的病人已经发病5天，腹痛稍有减轻但仍然发热，在体检时发现右下腹有压痛的包块，此时应如何处理？" +### Response: +""" + +print(generate(model, prompt)) + + + +这个病人已经有五天的急性阑尾炎了，腹痛虽然有所缓解，但他还是发烧，这让我有点担心。再看看他的体检结果，右下腹有压痛的包块，这就让我更有理由担心。嗯，既然有包块，而且病人还是发烧，应该是急性阑尾炎的急性症状。 + +想到这些，我觉得应该马上处理一下。最好的办法就是立即做腹部超声检查，看看包块的具体情况。超声检查可以帮助我们了解包块的位置、大小、形态以及周围组织的状态，这些信息对治疗非常重要。 + +哦，对了，包块如果是液体的，可能就不需要手术了。我们可以通过超声检查来确定这一点。这样就能避免不必要的手术创伤。 + +但是如果包块是固体的，特别是当它对周围组织有压迫作用时，手术就变得必要了。我们需要根据包块的具体情况来决定是否手术。 + +另外，包块的形态和位置也会影响手术的选择。我们需要根据这些因素来制定具体的手术方案。 + +嗯，总结一下，首先必须做一个腹部超声检查，确定包块的类型和具体情况。只有在确认包块是固体并且对周围组织有压迫作用的时候，才需要考虑手术。 + +好的，这个思路看起来很合理。现在就要把这些想法转化为具体的处理步骤。 + +在这种情况下，建议首先进行腹部超声检查，以确定包块的类型和具体情况。根据检查结果： + +1. **如果包块是液体性包块**：通常不需要手术。可以通过药物治疗缓解症状，随后观察病情缓解情况。 + +2. **如果包块是固体性包块并且对周围组织有压迫作用**：这时手术就变得必要了。通常需要进行包块切除术，以解除压迫，缓解症状。 + +请尽快安排进行腹部超声检查，并根据检查结果制定最合适的手术方案。<｜end▁of▁sentence｜> \ No newline at end of file diff --git a/config.json b/config.json new file mode 100644 index 0000000..a4ba21b --- /dev/null +++ b/config.json @@ -0,0 +1,3 @@ +{ + "model_type": "llama" +} \ No newline at end of file diff --git a/unsloth.Q8_0.gguf b/unsloth.Q8_0.gguf new file mode 100644 index 0000000..e49d6ef --- /dev/null +++ b/unsloth.Q8_0.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b1607e172a2bbd53ce28d5e87fb5135f067026b399b8962d8ed78a3eea4b5abb +size 8540773152