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Llama-3.1-8B-Instruct-AQLM-8bit-8x8 – AI Model by dbw6 | AlphaNeural AI

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dbw6/
Llama-3.1-8B-Instruct-AQLM-8bit-8x8

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text-generation

llama-31-8b-instruct

meta-llama/Llama-3.1-8B-Instruct

text-generation-inference

endpoints_compatible

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dbw6/Llama-3.1-8B-Instruct-AQLM-8bit-8x8

This repository contains a Hugging Face export of Llama-3.1-8B-Instruct quantized with AQLM using the 8-bit 8x8 scheme.

Base model

meta-llama/Llama-3.1-8B-Instruct

Quantization

Method: AQLM
Scheme: 8x8
Effective label: 8-bit
Source checkpoint: /work/bduan1/quantized_models/Llama-3.1-8B-Instruct-AQLM-8bit-8x8-n4096

Conversion

This repo was produced with convert_to_hf.py from the AQLM project, then exported with --save_safetensors and --save_tokenizer.

Inference requires a Transformers version with AQLM quantization support and the aqlm package installed in the runtime environment.

Local Evaluation

Wikitext2 perplexity: 6.5135
C4 perplexity: 8.0386
Calibration data: 4096 RedPajama samples tokenized with the meta-llama/Llama-3.1-8B-Instruct tokenizer at sequence length 8192
AQLM settings: num_codebooks=8, nbits_per_codebook=8, in_group_size=8, out_group_size=1

Usage

python

from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "dbw6/Llama-3.1-8B-Instruct-AQLM-8bit-8x8"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype="auto",
    device_map="auto",
    trust_remote_code=True,
)