You can deploy this model and start earning money today!

rizkysulaeman/
llama-3.2-3B-reasoning-en-ft-v1

Name: llama-3.2-3B-reasoning-en-ft-v1
Availability: InStock

Views

No views yet

CALISTA-INDUSTRY/llama-3.2-3B-reasoning-en-ft-v1

Model Summary

CALISTA-INDUSTRY/llama-3.2-3B-reasoning-en-ft-v1 is a fine-tuned version of Meta's LLaMA 3 3B model, optimized for English-language reasoning tasks. This model has been adapted to enhance performance in logical reasoning, problem-solving, and conversational understanding.

Model Details

Developed by: Mohammad Yani & Rizky Sulaeman, Politeknik Negeri Indramayu
Model type: Decoder-only transformer (LLaMA 3 architecture)
Parameter count: 3.21 billion
Quantization formats: 4-bit (Q4_K_M), 5-bit (Q5_K_M), 8-bit (Q8_0)
Training data: [Specify datasets or data sources used]
License: Apache License 2.0
Base model: meta-llama/Llama-3-3B

Intended Uses & Limitations

Intended Uses

Applications:
- Logical reasoning tasks
- Conversational agents requiring enhanced reasoning capabilities
- Educational tools focusing on critical thinking
Users:
- Researchers in natural language processing
- Developers building AI-driven applications
- Educators and students in AI-related fields

Limitations

The model's performance may degrade on tasks outside its fine-tuned domain.
Not suitable for real-time applications without further optimization.
May produce incorrect or nonsensical answers; outputs should be verified in critical applications.

How to Use

python

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="CALISTA-INDUSTRY/llama-3.2-3B-reasoning-en-ft-v1")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

rizkysulaeman/llama-3.2-3B-reasoning-en-ft-v1