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Model: Shubhankar444/smolified-ingredient-extractor
Source: Original Platform

README.md

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+---
+license: apache-2.0
+language:
+- en
+tags:
+- text-generation-inference
+- transformers
+- smolify
+- dslm
+pipeline_tag: text-generation
+inference:
+  parameters:
+    temperature: 1
+    top_p: 0.95
+    top_k: 64
+---
+
+# 🤏 smolified-ingredient-extractor
+
+> **Intelligence, Distilled.**
+
+This is a **Domain Specific Language Model (DSLM)** generated by the **Smolify Foundry**.
+
+It has been synthetically distilled from SOTA reasoning engines into a high-efficiency architecture, optimized for deployment on edge hardware (CPU/NPU) or low-VRAM environments.
+
+## 📦 Asset Details
+- **Origin:** Smolify Foundry (Job ID: `22fdd899`)
+- **Architecture:** gemma-3-270m
+- **Training Method:** Proprietary Neural Distillation
+- **Optimization:** 4-bit Quantized / FP16 Mixed
+- **Dataset:** [Link to Dataset](https://huggingface.co/datasets/Shubhankar444/smolified-ingredient-extractor)
+
+## 🚀 Usage (Inference)
+This model is compatible with standard inference backends like vLLM, and Hugging Face Transformers.
+
+```python
+# Example: Running your Sovereign Model
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = "Shubhankar444/smolified-ingredient-extractor"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto")
+
+messages = [
+    {"role": "system", "content": '''Extract ingredients from the Indian recipe and return as a Python list.'''},
+    {"role": "user", "content": '''Prepare Bhindi Masala by slicing okra and shallow frying in vegetable oil. Keep aside. In the same pan, saute onions and tomatoes with cumin, coriander powder, dry mango powder, and salt. Add the okra back in and toss well until the vegetables are soft. Serve with hot roti.'''}
+]
+text = tokenizer.apply_chat_template(
+    messages,
+    tokenize = False,
+    add_generation_prompt = True,
+)
+if "gemma-3-270m" == "gemma-3-270m":
+    text = text.removeprefix('<bos>')
+
+from transformers import TextStreamer
+_ = model.generate(
+    **tokenizer(text, return_tensors = "pt").to(model.device),
+    max_new_tokens = 1000,
+    temperature = 1.0, top_p = 0.95, top_k = 64,
+    streamer = TextStreamer(tokenizer, skip_prompt = True),
+)
+```
+
+## ⚖️ License & Ownership
+This model weights are a sovereign asset owned by **Shubhankar444**.
+Generated via [Smolify.ai](https://smolify.ai).
+
+[<img src="https://smolify.ai/smolify.gif" width="100"/>](https://smolify.ai)