Sponsored by
AdsCreator.com
Spestly / Athena-1-1.5B
Model's Last Updated: January 26 2025
text-generation
Introduction of Athena-1-1.5B
Model Details of Athena-1-1.5B
Athena-1 1.5B:
Athena-1 1.5B is a fine-tuned, instruction-following large language model derived from Qwen/Qwen2.5-1.5B-Instruct . Designed for efficiency and high-quality text generation, Athena-1 1.5B maintains a compact size, making it ideal for real-world applications where performance and resource efficiency are critical, such as lightweight applications, conversational AI, and structured data tasks.
Key Features
⚡ Lightweight and Efficient
- Compact Size: At just 1.5 billion parameters , Athena-1 1.5B offers excellent performance with reduced computational requirements.
- Instruction Following: Fine-tuned for precise and reliable adherence to user prompts.
- Coding and Mathematics: Proficient in solving coding challenges and handling mathematical tasks.
📖 Long-Context Understanding
- Context Length: Supports up to 32,768 tokens , enabling the processing of moderately lengthy documents or conversations.
- Token Generation: Can generate up to 8K tokens of output.
🌍 Multilingual Support
-
Supports
29+ languages
, including:
- English, Chinese, French, Spanish, Portuguese, German, Italian, Russian
- Japanese, Korean, Vietnamese, Thai, Arabic, and more.
📊 Structured Data & Outputs
- Structured Data Interpretation: Processes structured formats like tables and JSON.
- Structured Output Generation: Generates well-formatted outputs, including JSON and other structured formats.
Model Details
- Base Model: Qwen/Qwen2.5-1.5B-Instruct
- Architecture: Transformers with RoPE, SwiGLU, RMSNorm, Attention QKV bias, and tied word embeddings.
- Parameters: 1.5B total (Adjust non-embedding count if you have it).
- Layers: (Adjust if different from the 3B model)
- Attention Heads: (Adjust if different from the 3B model)
- Context Length: Up to 32,768 tokens .
Applications
Athena 1.5B is designed for a variety of real-world applications:
- Conversational AI: Build fast, responsive, and lightweight chatbots.
- Code Generation: Generate, debug, or explain code snippets.
- Mathematical Problem Solving: Assist with calculations and reasoning.
- Document Processing: Summarize and analyze moderately large documents.
- Multilingual Applications: Support for global use cases with diverse language requirements.
- Structured Data: Process and generate structured data, such as tables and JSON.
Quickstart
Here’s how you can use Athena 1.5B for quick text generation:
# Use a pipeline as a high-level helper
from transformers import pipeline
messages = [
{"role": "user", "content": "Who are you?"},
]
pipe = pipeline("text-generation", model="Spestly/Athena-1-1.5B") # Update model name
print(pipe(messages))
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("Spestly/Athena-1-1.5B") # Update model name
model = AutoModelForCausalLM.from_pretrained("Spestly/Athena-1-1.5B") # Update model name
Runs of Spestly Athena-1-1.5B on huggingface.co
2
Total runs
0
24-hour runs
-1
3-day runs
-1
7-day runs
-14
30-day runs
More Information About Athena-1-1.5B huggingface.co Model
Url of Athena-1-1.5B
Athena-1-1.5B huggingface.co Url
Provider of Athena-1-1.5B huggingface.co
Other API from Spestly
Total runs:
120
Run Growth:
-116
Growth Rate:
-96.67%
Total runs:
50
Run Growth:
9
Growth Rate:
18.00%
Total runs:
27
Run Growth:
-54
Growth Rate:
-200.00%
Total runs:
26
Run Growth:
0
Growth Rate:
0.00%
Total runs:
11
Run Growth:
-278
Growth Rate:
-2527.27%
Total runs:
7
Run Growth:
-146
Growth Rate:
-2085.71%
Total runs:
4
Run Growth:
-8
Growth Rate:
-200.00%
Total runs:
3
Run Growth:
-25
Growth Rate:
-833.33%
Total runs:
2
Run Growth:
-23
Growth Rate:
-1150.00%
Total runs:
1
Run Growth:
0
Growth Rate:
0.00%
Total runs:
0
Run Growth:
0
Growth Rate:
0.00%