Update README.md

README.md

@@ -1,199 +1,151 @@
 ---
 library_name: transformers
-tags: []
+tags:
+- code
+- agent
+- agentic
+- highperformance
+- moe
+- mixtureofexperts
+- glm4.7
+- fast
+- reasoning
+license: mit
+datasets:
+- aaravriyer193/Chimp-GPT-Code-Refined-12k
+language:
+- en
+base_model:
+- zai-org/GLM-4.7-Flash
 ---
+#
 
-# Model Card for Model ID
+```text
+=============================================================================
+   ____ _     _                 ____ ____ _____   ____          _           
+  / ___| |__ (_)_ __ ___  _ __ / ___|  _ \_   _| / ___|___   __| | ___ _ __ 
+ | |   | '_ \| | '_ ` _ \| '_ \ |  _| |_) || |  | |   / _ \ / _` |/ _ \ '__|
+ | |___| | | | | | | | | | |_) | |_| |  __/| |  | |__| (_) | (_| |  __/ |   
+  \____|_| |_|_|_| |_| |_| .__/ \____|_|   |_|   \____\___/ \__,_|\___|_|   
+                         |_|                                                
+                          _____ _ _ _       
+                         | ____| (_) |_ ___ 
+                         |  _| | | | __/ _ \
+                         | |___| | | ||  __/
+                         |_____|_|_|\__\___|
+=============================================================================
+````
 
-<!-- Provide a quick summary of what the model is/does. -->
+\<div align="center"\>
 
+*Provide concise, bug-free, and high-performance code.*
 
+\</div\>
 
-## Model Details
+-----
 
-### Model Description
+## 🦍 Overview
 
-<!-- Provide a longer summary of what this model is. -->
+**ChimpGPT-Coder-Elite** is a state-of-the-art, fine-tuned programming assistant built on the massive 30B parameter GLM-4.7-Flash Mixture-of-Experts (MoE) architecture.
 
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+It has been rigorously trained on a highly refined, 12,000-sample dataset (`Chimp-GPT-Code-Refined-12k`) to eradicate conversational boilerplate, hallucinated syntax, and context-loss. It does one thing, and it does it with lethal precision: **it writes elite-level code.**
 
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
+### ⚡ Key Features
 
-### Model Sources [optional]
+  * **Zero-Shot Alignment:** Hard-wired to bypass chatbot pleasantries and deliver structural code immediately.
+  * **16k Context Window:** Flawlessly handles long-range file refactoring without losing variable logic.
+  * **MoE Routing Mastery:** Hyper-optimized expert routing for logic-dense languages (Python, Rust, TS, C++).
+  * **VRAM Efficient:** Fully merged weights optimized for blazing-fast 4-bit inference on NVIDIA L4 (24GB) and A100 GPUs.
 
-<!-- Provide the basic links for the model. -->
+-----
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+## 🚀 Quickstart (Inference)
 
-## Uses
+ChimpGPT-Coder-Elite is merged and ready for immediate deployment. You do not need `peft` to run this model.
 
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+### Prerequisites
 
-### Direct Use
+```bash
+pip install torch transformers accelerate bitsandbytes
+```
 
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+### Python CLI Snippet (L4 / A100 Optimized)
 
-[More Information Needed]
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
 
-### Downstream Use [optional]
+MODEL_ID = "aaravriyer193/chimpgpt-coder-elite"
+SYSTEM_PROMPT = "You are Coder-Elite, a world-class programming assistant. Provide concise, bug-free, and high-performance code."
 
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+# 1. Load Tokenizer
+tokenizer = AutoTokenizer.from_pretrained(MODEL_ID, trust_remote_code=True)
 
-[More Information Needed]
+# 2. Strict 4-bit Configuration
+bnb_config = BitsAndBytesConfig(
+    load_in_4bit=True,
+    bnb_4bit_use_double_quant=True,
+    bnb_4bit_quant_type="nf4",
+    bnb_4bit_compute_dtype=torch.bfloat16 
+)
 
-### Out-of-Scope Use
+# 3. Load Model (Direct to VRAM)
+model = AutoModelForCausalLM.from_pretrained(
+    MODEL_ID,
+    quantization_config=bnb_config,
+    device_map={"": 0}, # Bypasses CPU offload errors
+    trust_remote_code=True,
+    attn_implementation="sdpa" 
+)
+model.eval()
 
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+# 4. Generate
+user_input = "Write a high-performance FastAPI endpoint with background tasks."
+prompt = f"<|system|>\n{SYSTEM_PROMPT}\n<|user|>\n{user_input}\n<|assistant|>\n"
 
-[More Information Needed]
+inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
 
-## Bias, Risks, and Limitations
+with torch.no_grad():
+    outputs = model.generate(
+        **inputs,
+        max_new_tokens=1024,
+        do_sample=True,
+        temperature=0.1, # Strict logic mode
+        top_p=0.9,
+        eos_token_id=tokenizer.eos_token_id
+    )
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+response = tokenizer.decode(outputs[0][len(inputs["input_ids"][0]):], skip_special_tokens=True)
+print(response)
+```
 
-[More Information Needed]
+-----
 
-### Recommendations
+## 🧠 Training Architecture
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+This model was trained using a custom hardware-aligned pipeline on an NVIDIA A100.
 
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+  * **Method:** Low-Rank Adaptation (LoRA)
+  * **Rank (r):** 64
+  * **Alpha:** 128
+  * **Target Modules:** `all-linear`
+  * **Learning Rate:** 2e-4 (Cosine Scheduler)
+  * **Precision:** `bfloat16` with 4-bit quantized base weights during training.
+  * **Final Loss:** \< 0.60 (Targeting the structural "Goldilocks Zone" to prevent overfitting).
 
-## How to Get Started with the Model
+### Dataset
 
-Use the code below to get started with the model.
+Trained exclusively on [aaravriyer193/Chimp-GPT-Code-Refined-12k](https://www.google.com/search?q=https://huggingface.co/datasets/aaravriyer193/Chimp-GPT-Code-Refined-12k). The dataset was formatted using a strict `<|system|>`, `<|user|>`, `<|assistant|>` chat template to enforce structural discipline.
 
-[More Information Needed]
+-----
 
-## Training Details
+## ⚠️ Limitations & Hardware Requirements
 
-### Training Data
+  * **VRAM Minimum:** Running this model requires at least **20GB of VRAM** (e.g., NVIDIA L4, RTX 3090, RTX 4090) when using 4-bit quantization.
+  * **Precision:** The model was explicitly merged in `bfloat16`. Attempting to load this in `float32` will result in massive Out-of-Memory (OOM) errors.
 
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+-----
 
-[More Information Needed]
-
-### Training Procedure
-
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-
-#### Preprocessing [optional]
-
-[More Information Needed]
-
-
-#### Training Hyperparameters
-
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
-
-## Evaluation
-
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
-### Results
-
-[More Information Needed]
-
-#### Summary
-
-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
-
-[More Information Needed]
-
-#### Hardware
-
-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Model Card Authors [optional]
-
-[More Information Needed]
-
-## Model Card Contact
-
-[More Information Needed]
+\<div align="center"\>
+\<i\>Trained with 🍌 by aaravriyer193\</i\>
+\</div\>