Update README.md

README.md

@@ -1,199 +1,204 @@
 ---
 library_name: transformers
-tags: []
+license: mit
+datasets:
+- SciPhi/textbooks-are-all-you-need-lite
+- nampdn-ai/tiny-textbooks
+- nampdn-ai/tiny-strange-textbooks
+- nampdn-ai/tiny-codes
+- nampdn-ai/tiny-math-textbooks
+- nampdn-ai/tiny-webtext
+- nampdn-ai/tiny-orca-textbooks
+- nampdn-ai/tiny-lessons
+- roneneldan/TinyStories
+- ajibawa-2023/Children-Stories-Collection
+- ajibawa-2023/General-Stories-Collection
+- kerinin/hackernews-stories
+- lucadiliello/wikipedia_512_pretraining
+- Salesforce/wikitext
+- ChristophSchuhmann/basic-math-problems-with-step-by-step-solutions
+- iamtarun/python_code_instructions_18k_alpaca
+- prithivMLmods/Step-Instruction-Gx
+- LinhDuong/chatdoctor-200k
+- MBZUAI/LaMini-instruction
+- qwedsacf/grade-school-math-instructions
+- TigerResearch/tigerbot-stackexchange-qa-en-0.5m
+language:
+- en
 ---
 
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
+# amusktweewt/tiny-model-500M-chat-v2
 
+This model is a general-purpose transformer-based language model designed for tasks such as text generation, story writing, and conversational interactions. It leverages multiple curated datasets to enhance its storytelling, coding, and question-answering capabilities. This project is intended for academic research and educational purposes only. It is designed for experimentation, learning, and development of language-based AI systems.
 
 ## Model Details
 
 ### Model Description
 
-<!-- Provide a longer summary of what this model is. -->
-
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
-
-- **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]
+The model was developed with a focus on balancing performance and computational efficiency. It employs **flash attention** and other optimizations to improve memory efficiency and speed.
 
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Developed by:** amusktweewt
+- **Model type:** LlamaForCausalLM
+- **Architectural Details:**
+  - 12 layers
+  - 16 attention heads
+  - Hidden size: 1536
+  - Flash attention 2 enabled
+  - Dynamic RoPE scaling
+- **License:** MIT
+- **Language(s) (NLP):** English
 
 ## Uses
 
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
 ### Direct Use
 
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
+This model is intended for text generation, code completion, chat-based applications, and story writing.
 
 ### Out-of-Scope Use
 
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
-
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-
-## How to Get Started with the Model
-
-Use the code below to get started with the model.
-
-[More Information Needed]
+- Tasks requiring high factual accuracy
+- Math or thinking related tasks
+- Applications involving sensitive content without human review
 
 ## Training Details
 
 ### Training Data
 
-<!-- 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. -->
+The model was trained on a diverse collection of datasets, including:
 
-[More Information Needed]
+- Textbooks and academic content
+- Creative and children's stories
+- Coding instruction datasets
+- Wiki-based texts and general stories
+- Mathematics and step-by-step solutions
 
 ### 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]
-
+#### Preprocessing
 
-#### Training Hyperparameters
+- Custom BPE tokenizer with a vocabulary size of 32,768
+- Applied dynamic RoPE scaling for better long-context handling
 
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+#### Hyperparameters
 
-#### Speeds, Sizes, Times [optional]
+- **Batch size:** 12 (per device)
+- **Gradient accumulation:** 2 steps
+- **Learning rate:** 1e-5
+- **Weight decay:** 0.002
+- **Warmup ratio:** 10%
+- **Precision:** FP16 (mixed precision)
 
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+#### Training Setup
 
-[More Information Needed]
+- **Hardware:** NVIDIA 4090 GPU
+- **Training Time:** 216 hours
+- **Dataset Size** 69 GB of Text
 
 ## 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]
+The model was evaluated using subsets of the training data, focusing on language coherence, relevancy, and fluency.
 
 #### Metrics
 
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
+- **Loss:** Evaluated based on token-level prediction accuracy.
+- **Perplexity:** 2.506
 
 ### Results
 
-[More Information Needed]
+The model generates coherent and most of the time contextually appropriate outputs across multiple domains.
 
-#### Summary
+## Risks and Limitations
 
+### Known Issues
 
+- The model may produce outputs reflecting biases present in the training data.
 
-## 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 -->
+### Recommendations
 
-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).
+Users should apply human review when using the model in critical or sensitive applications.
 
-- **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]
+## How to Get Started with the Model
 
-## Technical Specifications [optional]
+```python
+import torch
+from transformers import pipeline, set_seed
+
+model_name = "amusktweewt/tiny-model-500M-chat-v2"
+chatbot = pipeline(
+    "text-generation",
+    model=model_name,
+    device=0
+)
+
+set_seed(42)
+
+print("Chatbot is ready! Type 'exit' to end the conversation.")
+
+while True:
+    user_input = input("You: ").strip()
+    if user_input.lower() == "exit":
+        print("Exiting chat. Goodbye!")
+        break
+
+    messages = [
+        {"role": "user", "content": user_input},
+        {"role": "assistant", "content": ""}
+    ]
+
+    prompt = chatbot.tokenizer.apply_chat_template(messages, tokenize=False)
+
+    # Generate text using the formatted prompt.
+    response = chatbot(
+        prompt,
+        do_sample=True,
+        max_new_tokens=512,
+        top_k=50,
+        temperature=0.1,
+        num_return_sequences=1,
+        repetition_penalty=1.1,
+        pad_token_id=chatbot.tokenizer.eos_token_id,
+        min_new_tokens=0
+    )
+
+    full_text = response[0]["generated_text"]
+    bot_response = full_text[len(prompt):].strip()
+    print(f"Bot: {bot_response}")
+```
+
+## Technical Specifications
 
 ### Model Architecture and Objective
 
-[More Information Needed]
+The model follows a **Transformer-based architecture** optimized for causal language modeling tasks.
 
-### Compute Infrastructure
+- Attention heads: 16
+- Hidden size: 1536
+- Flash attention and memory-efficient attention enabled
 
-[More Information Needed]
+### Compute Infrastructure
 
 #### Hardware
 
-[More Information Needed]
+- Single GPU (NVIDIA 4090)
 
 #### 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]
+- Python 3.8+
+- HuggingFace Transformers 4.48.0
+- PyTorch 2.4
 
-**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]
+## Environmental Impact
 
-[More Information Needed]
+- **Training Hours:** 216 hours
+- **Hardware:** NVIDIA 4090
+- **Carbon Emitted:** 9.07 kg CO2 eq
 
-## Model Card Authors [optional]
+## Model Card Authors
 
-[More Information Needed]
+amusktweewt
 
 ## Model Card Contact
 
-[More Information Needed]
+For questions or feedback, contact amusktweewt.