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The pipeline tag "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
🦟 Mosquito - Tiny Knowledge Model
A 7.3M parameter T5-based model that answers general knowledge questions. Smaller than a mosquito's brain, but surprisingly capable!
✨ Highlights
| Feature | Value |
|---|---|
| Parameters | 7,263,744 |
| Architecture | T5 v1.1 (Gated FFN) |
| Size (FP32) | 29 MB |
| Size (quantized + compressed) | ~6 MB |
| Training | Knowledge distillation |
| License | Apache 2.0 |
🚀 Quick Start
from transformers import T5ForConditionalGeneration, AutoTokenizer
model = T5ForConditionalGeneration.from_pretrained("ag14850/Mosquito")
tokenizer = AutoTokenizer.from_pretrained("google/t5-v1_1-base", legacy=False)
def ask(question):
inputs = tokenizer(f"question: {question}", return_tensors="pt", max_length=128, truncation=True)
outputs = model.generate(
**inputs,
max_new_tokens=24,
num_beams=6,
no_repeat_ngram_size=2,
repetition_penalty=20.0,
early_stopping=True
)
return tokenizer.decode(outputs[0], skip_special_tokens=True)
print(ask("Why is the sky blue?"))
# Rayleigh scattering scatters blue wavelengths, causing blue wavelengths.
📊 Example Outputs
| Question | Answer |
|---|---|
| Why is the sky blue? | Rayleigh scattering scatters blue wavelengths, causing blue wavelengths. |
| How do vaccines work? | Vaccines stimulate the immune system to recognize and fight specific pathogens. |
| What is gravity? | Gravity is the force exerted by a planet's gravitational pull. |
| How does photosynthesis work? | Photosynthesis converts light energy into chemical energy through photosynthesis. |
| What causes earthquakes? | Earthquakes occur when tectonic plates slide past each other, causing earthquakes. |
| How do bees make honey? | Bees collect nectar from flowers, converting it into honey. |
| What is democracy? | Democracy is a form of government in which citizens vote for representatives. |
| Why do we dream? | Dreams are thought to help process emotions and consolidate memories. |
🏗️ Architecture
Model tree for ag14850/Mosquito
Base model
google/t5-v1_1-base