mo35
/

gemma4-quantfin-lora

@@ -1,200 +1,55 @@
 ---
-library_name: transformers
 tags:
 - unsloth
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 ---
+base_model: google/gemma-4-E4B-it
+license: gemma
+language:
+- en
 tags:
+- quantitative-finance
+- lora
 - unsloth
+- gemma4
+pipeline_tag: text-generation
 ---
+# Gemma 4 E4B — Quantitative Finance (LoRA)
+Fine-tuné sur 24 exemples Q&A de finance quantitative via QLoRA (rank=32).
+## Erreurs du modèle de base corrigées
+| Erreur | Correction |
+|---|---|
+| SABR attribué à HJM | Hagan, Kumar, Lesniewski & Woodward (2002) |
+| SABR vol avec mean-reversion | GBM log-normal sans drift |
+| Bergomi = CIR/Heston | Forward variance curve ξᵗᵤ |
+| Formule SABR inventée | Formule exacte avec z, χ(z) |
+## Entraînement
+| Paramètre | Valeur |
+|---|---|
+| GPU | RTX PRO 4500 (31.9 GB VRAM) |
+| Méthode | QLoRA 4-bit |
+| LoRA rank | 32 |
+| LoRA alpha | 64 |
+| Dataset | [mo35/quant-finance-dataset](https://huggingface.co/datasets/mo35/quant-finance-dataset) |
+| Epochs | 10 |
+| Loss finale | 2.5583 |
+## Utilisation rapide
+```python
+from unsloth import FastModel
+model, tokenizer = FastModel.from_pretrained(
+    "mo35/gemma4-quantfin-lora", max_seq_length=4096, load_in_4bit=True
+)
+FastModel.for_inference(model)
+inputs = tokenizer.apply_chat_template(
+    [{"role": "user", "content": "Derive the SABR implied volatility formula."}],
+    return_tensors="pt", add_generation_prompt=True
+).to("cuda")
+print(tokenizer.decode(model.generate(inputs, max_new_tokens=1024)[0][inputs.shape[-1]:],
+                       skip_special_tokens=True))
+```