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 *.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

README.md

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+---
+base_model: microsoft/Phi-4-mini-instruct
+library_name: peft
+tags:
+  - text-generation
+  - instruction-tuning
+  - lora
+  - fine-tuned
+  - phi-4
+  - pytorch
+  - transformers
+license: mit
+language:
+  - en
+pipeline_tag: text-generation
+inference: true
+---
+
+# Model Card for Phi-4 LoRA Fine-tuned Model
+
+This model is a LoRA fine-tuned version of Microsoft's Phi-4-mini-instruct, optimized for improved code review using GitHub data.
+
+## Model Details
+
+### Model Description
+
+This is a fine-tuned version of Microsoft's Phi-4-mini-instruct model using LoRA (Low-Rank Adaptation) technique. The model has been trained on 10k instruction-response pairs to enhance its ability to follow instructions and generate high-quality responses across various tasks.
+
+The model uses 4-bit quantization with NF4 for efficient inference while maintaining performance quality. It's designed to be a lightweight yet capable language model suitable for various text generation tasks.
+
+- **Developed by:** Milos Kotlar
+- **Model type:** Causal Language Model
+- **Language(s) (NLP):** English
+- **License:** MIT
+- **Finetuned from model:** microsoft/Phi-4-mini-instruct
+
+### Model Sources
+
+- **Repository:** https://github.com/kotlarmilos/phi4-finetuned
+- **Demo:** https://huggingface.co/spaces/kotlarmilos/dotnet-runtime
+
+## Uses
+
+### Direct Use
+
+The model is designed for:
+
+- **Instruction Following**: Generate responses to user instructions and queries
+- **Conversational AI**: Engage in multi-turn conversations
+- **Task Completion**: Help with various text-based tasks like summarization, explanation, and creative writing
+- **Educational Support**: Provide explanations and assistance for learning
+
+### Downstream Use
+
+The model can be integrated into:
+
+- **Chatbot Applications**: Web applications, mobile apps, and customer service systems
+- **Content Generation Tools**: Writing assistants and creative content platforms
+- **Educational Platforms**: Tutoring systems and interactive learning environments
+- **API Services**: Text generation services and intelligent automation workflows
+
+### Out-of-Scope Use
+
+The model is **not intended for**:
+
+- **Factual Information Retrieval**: May generate plausible but incorrect information
+- **Professional Medical/Legal Advice**: Not qualified for specialized professional guidance
+- **Real-time Critical Systems**: Not suitable for safety-critical applications
+- **Harmful Content Generation**: Should not be used to create misleading, harmful, or malicious content
+
+## How to Get Started with the Model
+
+```python
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
+from peft import PeftModel
+
+# Load base model with quantization
+base_model = "kotlarmilos/Phi-4-mini-instruct"
+lora_path = "artifacts/phi4-finetuned"
+
+bnb_config = BitsAndBytesConfig(
+    load_in_4bit=True,
+    bnb_4bit_quant_type="nf4",
+    bnb_4bit_use_double_quant=True,
+    bnb_4bit_compute_dtype=torch.bfloat16,
+)
+
+tokenizer = AutoTokenizer.from_pretrained(base_model, use_fast=True)
+
+base = AutoModelForCausalLM.from_pretrained(
+    base_model,
+    quantization_config=bnb_config,
+    device_map="auto",
+    trust_remote_code=True
+)
+
+# Load LoRA adapter
+model = PeftModel.from_pretrained(base, lora_path)
+
+# Generate text
+def generate(prompt):
+    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+    output = model.generate(
+        **inputs, 
+        max_new_tokens=256, 
+        do_sample=True, 
+        temperature=0.7,
+        pad_token_id=tokenizer.eos_token_id
+    )
+    return tokenizer.decode(output[0], skip_special_tokens=True)
+
+# Example usage
+prompt = "Review the following code changes:"
+response = generate(prompt)
+print(response)
+```
+
+## Training Details
+
+### Training Data
+
+The model was fine-tuned on approximately 10,000 high-quality instruction-response pairs designed to improve the model's ability to follow instructions and generate helpful, accurate responses across various domains.
+
+**Data Characteristics**:
+- **Size**: ~10,000 instruction-response pairs
+- **Format**: Structured instruction-following conversations
+- **Coverage**: Diverse topics and instruction types
+
+### Training Procedure
+
+#### Preprocessing
+
+1. **Data Preparation**: Instruction-response pairs formatted for causal language modeling
+2. **Tokenization**: Text processed using Phi-4's tokenizer with appropriate special tokens
+3. **Sequence Formatting**: Proper formatting for instruction-following tasks
+4. **Quality Filtering**: Removal of low-quality or potentially harmful content
+
+#### Training Hyperparameters
+
+**LoRA Configuration**:
+- **LoRA Rank (r)**: 8
+- **LoRA Alpha**: 16
+- **LoRA Dropout**: 0.05
+- **Target Modules**: ["qkv_proj", "gate_up_proj"]
+- **Task Type**: CAUSAL_LM
+
+**Training Setup**:
+- **Base Model**: microsoft/Phi-4-mini-instruct
+- **Training Method**: LoRA (Low-Rank Adaptation)
+- **Quantization**: 4-bit NF4 with BitsAndBytes
+- **Training regime**: Mixed precision training with appropriate optimization

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "microsoft/Phi-4-mini-instruct",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "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",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "qkv_proj",
+    "gate_up_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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+size 28328760

added_tokens.json

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+{
+  "<|/tool_call|>": 200026,
+  "<|/tool|>": 200024,
+  "<|assistant|>": 200019,
+  "<|end|>": 200020,
+  "<|system|>": 200022,
+  "<|tag|>": 200028,
+  "<|tool_call|>": 200025,
+  "<|tool_response|>": 200027,
+  "<|tool|>": 200023,
+  "<|user|>": 200021
+}

chat_template.jinja

@@ -0,0 +1 @@
+{% for message in messages %}{% if message['role'] == 'system' and 'tools' in message and message['tools'] is not none %}{{ '<|' + message['role'] + '|>' + message['content'] + '<|tool|>' + message['tools'] + '<|/tool|>' + '<|end|>' }}{% else %}{{ '<|' + message['role'] + '|>' + message['content'] + '<|end|>' }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|assistant|>' }}{% else %}{{ eos_token }}{% endif %}

special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": "<|endoftext|>",
+  "unk_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.json

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+size 15524375

tokenizer_config.json

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+{
+  "add_bos_token": false,
+  "add_eos_token": false,
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "199999": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
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+    "200021": {
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+    },
+    "200023": {
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+      "rstrip": true,
+      "single_word": false,
+      "special": false
+    },
+    "200027": {
+      "content": "<|tool_response|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": true,
+      "single_word": false,
+      "special": false
+    },
+    "200028": {
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+      "lstrip": false,
+      "normalized": false,
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+    }
+  },
+  "bos_token": "<|endoftext|>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|endoftext|>",
+  "extra_special_tokens": {},
+  "model_max_length": 131072,
+  "pad_token": "<|endoftext|>",
+  "tokenizer_class": "GPT2Tokenizer",
+  "unk_token": "<|endoftext|>"
+}

training_args.bin

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