Covenant-72B-Chat

Model Overview

Covenant-72B-Chat is the instruction-tuned variant of Covenant-72B, the largest permissionless collaboratively trained language model. It was fine-tuned via supervised fine-tuning (SFT) on top of the 72B-parameter base model.

For more details, see the technical report.

Usage

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained(
    "1Covenant/Covenant-72B-Chat",
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
tokenizer = AutoTokenizer.from_pretrained("1Covenant/Covenant-72B-Chat")

messages = [
    {"role": "user", "content": "Explain general relativity in simple terms."},
]
input_ids = tokenizer.apply_chat_template(messages, return_tensors="pt", add_generation_prompt=True).to(model.device)
output_ids = model.generate(input_ids, max_new_tokens=256)
print(tokenizer.decode(output_ids[0][input_ids.shape[-1]:], skip_special_tokens=True))

Model Details

• Base Model: Covenant-72B
• Fine-tuning: Supervised fine-tuning (SFT)
• Model License: Apache 2.0

Technical Specifications

Performance on Benchmarks

All values in (%). ARC-C is 25-shot, HellaSwag is 10-shot, BBH CoT is 3-shot, MATH is 4-shot; all others are 5-shot.

*strict; **acc. All others use acc_norm.

Additional Benchmarks

*exact_match; **prompt_strict. MuSR uses acc_norm.