aether-mini-v1 / README.md
RoeAcquisitions's picture
Upload README.md with huggingface_hub
fe084b8 verified
|
Raw
History Blame Contribute Delete
1.83 kB
---
language:
- en
library_name: transformers
pipeline_tag: text-generation
tags:
- text-generation
- qwen
- aether
- code-generation
inference: true
---
# Aether Mini V1
Aether Mini V1 is a fast, efficient 0.5B parameter language model optimized for general tasks, code generation, and instruction following. Based on Qwen2.5 architecture, fine-tuned for enterprise use cases.
## Features
- **Fast Inference**: Sub-second response times on consumer hardware
- **Code Generation**: Optimized for Python, JavaScript, TypeScript, and more
- **Instruction Following**: Fine-tuned for precise instruction adherence
- **Low Resource**: Runs on CPU with minimal memory requirements
## Usage
### Transformers
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("RoeAcquisitions/aether-mini-v1")
tokenizer = AutoTokenizer.from_pretrained("RoeAcquisitions/aether-mini-v1")
messages = [
{"role": "user", "content": "Write a Python function to calculate fibonacci numbers"}
]
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer([text], return_tensors="pt")
generated_ids = model.generate(**inputs, max_new_tokens=512)
response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
print(response)
```
### API
Access via Aether Tech AI API:
```bash
curl https://aether-models.nebulahq.work/v1/chat/completions \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "aether-mini-v1",
"messages": [{"role": "user", "content": "Hello"}]
}'
```
## Pricing
- **Input**: $0.10 per 1M tokens
- **Output**: $0.30 per 1M tokens
## License
Apache 2.0
## Contact
- Website: https://nebulahq.work
- Email: api@nebulahq.work