Upload GPT-2 LoRA model for recipe recommendations

- Added LoRA adapter weights (adapter_model.safetensors)
- Added adapter configuration (adapter_config.json)
- Added tokenizer files (tokenizer.json, vocab.json, merges.txt)
- Added model documentation and usage examples

README.md

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+---
+license: mit
+language: en
+tags:
+- recipe-recommendation
+- gpt2
+- lora
+- cooking
+- food
+base_model: gpt2
+---
+
+# Recipe GPT-2 LoRA Model
+
+A fine-tuned GPT-2 model for recipe recommendations using LoRA (Low-Rank Adaptation).
+
+## Model Description
+
+This model generates personalized recipe suggestions based on:
+- Available ingredients
+- Dietary preferences
+- Cooking time constraints
+- Cuisine preferences
+
+## Usage
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+from peft import PeftModel
+
+# Load base model and tokenizer
+base_model = AutoModelForCausalLM.from_pretrained("gpt2")
+tokenizer = AutoTokenizer.from_pretrained("gpt2")
+
+# Load LoRA adapter
+model = PeftModel.from_pretrained(base_model, "nutrientartcd/recipe-gpt2-lora")
+
+# Generate recipe suggestion
+prompt = "User: I have chicken, garlic, rice. I'm looking for something ready in about 30 minutes.\nAssistant: "
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=100, temperature=0.7)
+response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+print(response)
+```
+
+## Training Data
+
+Trained on a recipe dataset with user interactions and ratings, fine-tuned to provide conversational recipe recommendations.
+
+## Model Details
+
+- **Base Model**: GPT-2
+- **Fine-tuning Method**: LoRA (Low-Rank Adaptation)
+- **Training Framework**: Transformers + PEFT
+- **Language**: English
+- **Task**: Conversational recipe recommendation
+
+## Limitations
+
+- English language only
+- May generate fictional recipe names
+- Nutritional information not guaranteed to be accurate
+- Requires proper prompt format for optimal results
+
+## Prompt Format
+
+The model expects prompts in this conversation format:
+```
+User: I have [ingredients]. I'm looking for something ready in about [time] minutes. Preferences: [preferences].
+Assistant: 
+```
+
+## Citation
+
+If you use this model, please cite:
+```
+@misc{nutrient-recipe-gpt2-lora,
+  title={Recipe GPT-2 LoRA Model},
+  author={NutrientAI},
+  year={2025},
+  url={https://huggingface.co/nutrientartcd/recipe-gpt2-lora}
+}
+```

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "gpt2",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": true,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 16,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "qalora_group_size": 16,
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "c_fc",
+    "c_proj",
+    "c_attn"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:c7c81ce9c1d21ec3d2c94185dbfce7b58bb54f0c498d9638a7b25a06f38c9584
+size 4730632

special_tokens_map.json

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+{
+  "bos_token": "<|endoftext|>",
+  "eos_token": "<|endoftext|>",
+  "pad_token": "<|endoftext|>",
+  "unk_token": "<|endoftext|>"
+}

tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "50256": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<|endoftext|>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|endoftext|>",
+  "extra_special_tokens": {},
+  "model_max_length": 1024,
+  "pad_token": "<|endoftext|>",
+  "tokenizer_class": "GPT2Tokenizer",
+  "unk_token": "<|endoftext|>"
+}