Update README

README.md

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 ---
 license: mit
+datasets:
+- glaiveai/glaive-code-assistant-v2
+- TokenBender/code_instructions_122k_alpaca_style
+language:
+- en
+metrics:
+- code_eval
+pipeline_tag: text-generation
+tags:
+- code
+- text-generation-inference
 ---
+
+
+
+<p align="center">
+<img width="700px" alt="DeepSeek Coder" src="https://cdn-uploads.huggingface.co/production/uploads/64b566ab04fa6584c03b5247/5COagfF6EwrV4utZJ-ClI.png">
+</p>
+<hr>
+
+
+## 1. Introduction of CodeNinja
+
+CodeNinja is a fine tuned version of the excellent model [openchat/openchat-3.5-1210](https://huggingface.co/openchat/openchat-3.5-1210). It is a 7B model that was fine tuned using Supervised Fine Tuning in 2 instructions datasets containing in total more than 400 000 code instructions.
+
+The model is quite good for coding tasks and it's goal is to be a coding assistant that you can use daily.
+
+The quantized versions can be found here: [beowolx/CodeNinja-1.0-OpenChat-7B-GGUF](https://huggingface.co/beowolx/CodeNinja-1.0-OpenChat-7B-GGUF).
+
+The model performs very good in a serie of different tasks.
+
+- **Massive Training Data**: Fine-tuned using the datasets [glaiveai/glaive-code-assistant-v2](https://huggingface.co/datasets/glaiveai/glaive-code-assistant-v2) and [TokenBender/code_instructions_122k_alpaca_style](https://huggingface.co/datasets/TokenBender/code_instructions_122k_alpaca_style) it contains around 400 000 code instructions in different programming languages such as Python, C, C++, Rust, Java, JavaScript and etc.
+  
+- **Highly Flexible & Scalable**: Offered in model sizes of 7B, enabling users to run it locally.
+  
+- **Superior Model Performance**: State-of-the-art performance among publicly available code models on HumanEval.
+  
+- **Advanced Code Completion Capabilities**: A context window size of 8192 supporting project-level code completion.
+
+## 2. Prompt Format
+CodeNinja uses the same prompt format than OpenChat 3.5 so you will need to use it to get good results.
+
+The prompt format looks like this:
+
+```
+GPT4 Correct User: Hello<|end_of_turn|>GPT4 Correct Assistant: Hi<|end_of_turn|>GPT4 Correct User: How are you today?<|end_of_turn|>GPT4 Correct Assistant:
+```
+🚨 Notice: Remember to set `<|end_of_turn|>` as end of generation token.
+
+**You must use this prompt format to get good results**
+
+## 3. How to Use
+
+#### Using LM Studio
+The easiest way to start using the model is to download one of the [quantized](https://huggingface.co/beowolx/CodeNinja-1.0-OpenChat-7B-GGUF) versions
+using [LM Studio](https://lmstudio.ai/).
+
+You then need to make sure that you are using the "OpenChat" preset that contain the prompt format mentioned above already set.
+
+If you want, you can get the preset from this [gist](https://gist.github.com/beowolx/b219466681c02ff67baf8f313a3ad817).
+
+#### Using the transformers library
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+# Initialize the model
+model_path = "beowolx/CodeNinja-1.0-OpenChat-7B"
+model = AutoModelForCausalLM.from_pretrained(model_path, device_map="auto")
+# Import openchat tokenizer
+tokenizer = AutoTokenizer.from_pretrained("openchat/openchat-3.5-1210", use_fast=True)
+
+def generate_one_completion(prompt: str):
+    messages = [
+        {"role": "user", "content": prompt},
+        {"role": "assistant", "content": ""}  # Placeholder for the model's response
+    ]
+
+    # Apply the chat template to get the list of token IDs
+    input_ids = tokenizer.apply_chat_template(messages, add_generation_prompt=True)
+
+    # Generate completion
+    generate_ids = model.generate(
+        torch.tensor([input_ids]).to("cuda"),  # Convert list to tensor and send to GPU
+        max_length=256,
+        pad_token_id=tokenizer.pad_token_id,
+        eos_token_id=tokenizer.eos_token_id
+    )
+
+    # Decode and clean up the completion
+    completion = tokenizer.decode(generate_ids[0], skip_special_tokens=True)
+    completion = completion.split("\n\n\n")[0].strip()
+
+    return completion
+```
+
+## 4. License
+This code repository is licensed under the MIT License. The use of CodeNinja model is subject to the Model License.
+
+
+## 5. Contact
+
+If you have any questions, please raise an issue here.