| --- |
| license: apache-2.0 |
| language: |
| - en |
| base_model: |
| - TinyLlama/TinyLlama-1.1B-Chat-v1.0 |
| pipeline_tag: text-generation |
| tags: |
| - chemistry |
| - science |
| - physics |
| --- |
| # HamAI Science Model |
|
|
| A lightweight language model designed to answer science questions clearly and accurately in English. |
|
|
| --- |
|
|
| ## Overview |
|
|
| HamAI Science Model is trained and fine-tuned on science question–answer datasets. It is built to provide straightforward explanations across topics like physics, chemistry, and biology. |
|
|
| --- |
|
|
| ## Features |
|
|
| * Focused on science Q&A |
| * Clear and simple English answers |
| * Lightweight and efficient |
| * Suitable for educational use |
|
|
| --- |
|
|
| ## Usage |
|
|
| ```python |
| from transformers import AutoModelForCausalLM, AutoTokenizer |
| |
| model_name = "Haamipromax/HamAI-Science-1b" |
| |
| tokenizer = AutoTokenizer.from_pretrained(model_name) |
| model = AutoModelForCausalLM.from_pretrained(model_name) |
| |
| input_text = "Explain how quantum entanglement violates classical locality." |
| inputs = tokenizer(input_text, return_tensors="pt") |
| |
| outputs = model.generate(**inputs, max_new_tokens=100) |
| print(tokenizer.decode(outputs[0], skip_special_tokens=True)) |
| ``` |
|
|
| --- |
|
|
| ## Training Data |
|
|
| The model was trained on a mix of science question–answer datasets, including: |
|
|
| * General science questions |
| * Educational textbooks |
| * Scientific materials |
|
|
| --- |
|
|
| ## Limitations |
|
|
| * May produce incorrect answers outside science topics |
| * Not suitable for advanced research-level questions |
|
|
| --- |
|
|
| ## Intended Use |
|
|
| * Students learning science |
| * Simple question answering systems |
| * Educational tools and assistants |
|
|
| --- |
|
|
| ## License |
|
|
| Apache-2.0 |
