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Model: QuantaSparkLabs/Mimicer
Source: Original Platform

.gitattributes

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README.md

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+---
+license: apache-2.0
+language:
+  - en
+tags:
+  - assistant
+  - chatbot
+  - distilgpt2
+  - finetuned
+  - experimental
+  - mimicer
+pipeline_tag: text-generation
+library_name: transformers
+---
+
+<div align="center">
+
+# 🎭 Mimicer
+
+### *The model that learns to mirror.*
+
+**For fun!** 🚀
+
+</div>
+
+---
+
+## 🚀 Overview
+
+Mimicer is an experimental language model fine-tuned to reproduce text patterns and mirror user inputs.
+
+Unlike traditional assistants optimized for reasoning or instruction following, Mimicer explores identity mapping and response replication through supervised fine-tuning.
+
+This project serves as a learning platform for model training, dataset design, Hugging Face deployment, and transformer fine-tuning workflows.
+
+---
+
+## 📊 Model Details
+
+| Property         | Value                     |
+| ---------------- | ------------------------- |
+| Base Model       | DistilGPT2                |
+| Parameters       | 81.9M                     |
+| Architecture     | GPT-2 Decoder             |
+| Fine-Tuning      | Supervised                |
+| Training Samples | 2,500                     |
+| Context Length   | 40 Tokens                 |
+| Framework        | Hugging Face Transformers |
+| Hardware         | NVIDIA T4                 |
+| Repository       | QuantaSparkLabs/Mimicer   |
+
+---
+
+## ⚙️ Training Objective
+
+Training samples follow a structured format:
+
+```text
+Input: Hello world
+Output: Hello world
+```
+
+The objective is to teach the model to reproduce the provided text after the `Output:` prompt.
+
+Example:
+
+```text
+Input: How are you?
+Output: How are you?
+```
+
+---
+
+## 💻 Usage
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+model = AutoModelForCausalLM.from_pretrained(
+    "QuantaSparkLabs/Mimicer"
+)
+
+tokenizer = AutoTokenizer.from_pretrained(
+    "QuantaSparkLabs/Mimicer"
+)
+
+prompt = "Input: hello how are you\nOutput:"
+
+inputs = tokenizer(prompt, return_tensors="pt")
+
+outputs = model.generate(
+    **inputs,
+    max_new_tokens=20,
+    do_sample=False
+)
+
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+---
+
+## 🔬 Project Goals
+
+* Learn transformer fine-tuning
+* Understand dataset design
+* Explore identity-mapping behavior
+* Practice Hugging Face model deployment
+* Build a foundation for future custom models
+
+---
+
+## 📜 License
+
+Apache 2.0
+
+---
+
+<div align="center">
+
+### Built by QuantaSparkLabs
+
+</div>

config.json

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+{
+  "_num_labels": 1,
+  "activation_function": "gelu_new",
+  "add_cross_attention": false,
+  "architectures": [
+    "GPT2LMHeadModel"
+  ],
+  "attn_pdrop": 0.1,
+  "bos_token_id": 50256,
+  "dtype": "float32",
+  "embd_pdrop": 0.1,
+  "eos_token_id": 50256,
+  "id2label": {
+    "0": "LABEL_0"
+  },
+  "initializer_range": 0.02,
+  "label2id": {
+    "LABEL_0": 0
+  },
+  "layer_norm_epsilon": 1e-05,
+  "model_type": "gpt2",
+  "n_ctx": 1024,
+  "n_embd": 768,
+  "n_head": 12,
+  "n_inner": null,
+  "n_layer": 6,
+  "n_positions": 1024,
+  "pad_token_id": null,
+  "reorder_and_upcast_attn": false,
+  "resid_pdrop": 0.1,
+  "scale_attn_by_inverse_layer_idx": false,
+  "scale_attn_weights": true,
+  "summary_activation": null,
+  "summary_first_dropout": 0.1,
+  "summary_proj_to_labels": true,
+  "summary_type": "cls_index",
+  "summary_use_proj": true,
+  "task_specific_params": {
+    "text-generation": {
+      "do_sample": true,
+      "max_length": 50
+    }
+  },
+  "tie_word_embeddings": true,
+  "transformers_version": "5.10.2",
+  "use_cache": false,
+  "vocab_size": 50257
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 50256,
+  "eos_token_id": 50256,
+  "transformers_version": "5.10.2"
+}

model.safetensors

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tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": "<|endoftext|>",
+  "eos_token": "<|endoftext|>",
+  "errors": "replace",
+  "is_local": false,
+  "local_files_only": false,
+  "model_max_length": 1024,
+  "pad_token": "<|endoftext|>",
+  "tokenizer_class": "GPT2Tokenizer",
+  "unk_token": "<|endoftext|>"
+}

training_args.bin

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