Update README.md

README.md

@@ -1,3 +1,128 @@
 ---
 license: apache-2.0
+base_model: Felladrin/Minueza-32M-Base
+pipeline_tag: text-generation
+language:
+  - en
+datasets:
+  - HuggingFaceH4/ultrachat_200k
+  - Felladrin/ChatML-ultrachat_200k
+widget:
+  - messages:
+      - role: system
+        content: >-
+          You are a career counselor. The user will provide you with an individual looking for guidance in their professional life, and your task is to assist them in determining what careers they are most suited for based on their skills, interests, and experience. You should also conduct research into the various options available, explain the job market trends in different industries, and advice on which qualifications would be beneficial for pursuing particular fields.
+      - role: user
+        content: Heya!
+      - role: assistant
+        content: Hi! How may I help you?
+      - role: user
+        content: >-
+          I am interested in developing a career in software engineering. What
+          would you recommend me to do?
+  - messages:
+      - role: system
+        content: You are a highly knowledgeable assistant. Help the user as much as you can.
+      - role: user
+        content: How I can become a healthier person?
+  - messages:
+      - role: system
+        content: You are a helpful assistant who gives creative responses.
+      - role: user
+        content: Write the specs of a game about mages in a fantasy world.
+  - messages:
+      - role: system
+        content: You are a helpful assistant who answers user's questions with details.
+      - role: user
+        content: Tell me about the pros and cons of social media.
+  - messages:
+      - role: system
+        content: You are a helpful assistant who answers user's questions with details and curiosity.
+      - role: user
+        content: What are some potential applications for quantum computing?
+inference:
+  parameters:
+    max_new_tokens: 250
+    do_sample: true
+    temperature: 0.65
+    top_p: 0.55
+    top_k: 35
+    repetition_penalty: 1.176
 ---
+
+# Minueza-32M-UltraChat: A chat model with 32 million parameters
+
+- Base model: [Felladrin/Minueza-32M-Base](https://huggingface.co/Felladrin/Minueza-32M-Base)
+- Dataset: [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-ultrachat_200k)] [HuggingFaceH4/ultrachat_200k](https://huggingface.co/datasets/HuggingFaceH4/ultrachat_200k)
+- License: [Apache License 2.0](https://huggingface.co/Felladrin/Minueza-32M-UltraChat/resolve/main/license.txt)
+- Availability in other ML formats:
+  - GGUF: [Felladrin/gguf-Minueza-32M-UltraChat](https://huggingface.co/Felladrin/gguf-Minueza-32M-UltraChat)
+  - ONNX: [Felladrin/onnx-Minueza-32M-UltraChat](https://huggingface.co/Felladrin/onnx-Minueza-32M-UltraChat)
+
+## Recommended Prompt Format
+
+```
+<|im_start|>system
+{system_message}<|im_end|>
+<|im_start|>user
+{user_message}<|im_end|>
+<|im_start|>assistant
+```
+
+## Recommended Inference Parameters
+
+```yml
+do_sample: true
+temperature: 0.65
+top_p: 0.55
+top_k: 35
+repetition_penalty: 1.176
+```
+
+## Usage Example
+
+```python
+from transformers import pipeline
+
+generate = pipeline("text-generation", "Felladrin/Minueza-32M-UltraChat")
+
+messages = [
+    {
+        "role": "system",
+        "content": "You are a helpful assistant who answers the user's questions with details and curiosity.",
+    },
+    {
+        "role": "user",
+        "content": "What are some potential applications for quantum computing?",
+    },
+]
+
+prompt = generate.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+
+output = generate(
+    prompt,
+    max_new_tokens=256,
+    do_sample=True,
+    temperature=0.65,
+    top_k=35,
+    top_p=0.55,
+    repetition_penalty=1.176,
+)
+
+print(output[0]["generated_text"])
+```
+
+## How it was trained
+
+This model was trained with [SFTTrainer](https://huggingface.co/docs/trl/main/en/sft_trainer) using the following settings:
+
+| Hyperparameter         | Value                                         |
+| :--------------------- | :-------------------------------------------- |
+| Learning rate          | 2e-5                                          |
+| Total train batch size | 16                                            |
+| Max. sequence length   | 2048                                          |
+| Weight decay           | 0                                             |
+| Warmup ratio           | 0.1                                           |
+| Optimizer              | Adam with betas=(0.9,0.999) and epsilon=1e-08 |
+| Scheduler              | cosine                                        |
+| Seed                   | 42                                            |