Athena 3.1
Collection
Apache Labs' fine-tunes of the LlaMA 3.1 Family
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Athena 3.1 70B by Apache Labs
Athena 3.1 70B is a state-of-the-art language model developed by Apache Labs, based on Meta's Llama-3.1-70B. This fine-tuned model is designed for superior natural language understanding, advanced reasoning, and coherent text generation, suitable for a variety of professional, research, and creative tasks.
Model Overview
Athena 3.1 70B leverages the robust architecture of Llama-3.1-70B, tuned for high accuracy, nuanced comprehension, and reliable performance across diverse contexts. This model excels in tasks requiring deep language processing and logical coherence, making it a valuable tool for complex applications.
Key Features
- Enhanced Contextual Understanding: Maintains consistency across longer passages, providing accurate multi-turn responses.
- Advanced Reasoning Capabilities: Tuned to handle logical reasoning and complex question answering.
- Versatile Application: Effective across tasks such as content generation, research analysis, technical writing, and more.
Quickstart Guide
To get started with Athena 3.1 70B, you can use it in a Hugging Face environment with the following setup:
Use a pipeline as a high-level helper:
from transformers import pipeline
# Define the pipeline
pipe = pipeline("text-generation", model="apache-labs/Athena-3.1-70B")
# Define a prompt
messages = [
{"role": "user", "content": "Who are you?"},
]
# Generate response
response = pipe(messages)
print(response)
Load Model Directly:
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("apache-labs/Athena-3.1-70B")
model = AutoModelForCausalLM.from_pretrained("apache-labs/Athena-3.1-70B")
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Base model
meta-llama/Llama-3.1-70B