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base_model: /workspace/models/Mistral-Nemo-Base-2407
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer

load_in_8bit: false
# load_in_4bit: true
strict: false

datasets:
  - path: /workspace/datasets/dolphin-2.9.3/dolphin201-sharegpt2.jsonl

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from transformers import LlamaConfig as LC, LlamaForCausalLM as LLM, LlamaTokenizer as LT
from accelerate import init_empty_weights, load_checkpoint_and_dispatch
import torch
lt = LT.from_pretrained("NousResearch/Llama-2-7b-hf")
c = LC.from_pretrained("NousResearch/Llama-2-70b-hf")
c.max_position_embeddings = 32764
c.rope_theta = 1000000
with init_empty_weights(): m = LLM(c)
m = m.half().eval()
m.requires_grad_(False)

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#!/bin/sh

log() {
  format="$1"; shift
  # shellcheck disable=SC2059
  >&2 printf "$format\n" "$@"
}

usage() {
  >&2 cat <<EOF

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HP Smart Storage Admin CLI (ssacli) installation and usage on Proxmox PVE (6.x)

Why use HP Smart Storage Admin CLI?

You can use ssacli (smart storage administrator command line interface) tool to manage any of supported HP Smart Array Controllers in your Proxmox host without need to reboot your server to access Smart Storage Administrator in BIOS. That means no host downtime when managing your storage.

CLI is not as convenient as GUI interface provided by BIOS or desktop utilities, but still allows you to fully manage your controller, physical disks and logical drives on the fly with no Proxmox host downtime.

ssacli replaces older hpssacli, but shares the same syntax and adds support for newer servers and controllers.

Installation

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##VGG16 model for Keras

This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.

It has been obtained by directly converting the Caffe model provived by the authors.

Details about the network architecture can be found in the following arXiv paper:

Very Deep Convolutional Networks for Large-Scale Image Recognition

K. Simonyan, A. Zisserman