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#!/bin/bash

# Determine the HUBDIR based on the environment variables
if [[ -n "$HF_HUB_CACHE" ]]
then HUBDIR="$HF_HUB_CACHE"
elif [[ -n "$HF_HOME" ]]
then HUBDIR="$HF_HOME/hub"
else HUBDIR="$HOME/.cache/huggingface/hub/"
fi

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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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diff --git a/gguf-py/scripts/gguf-dump.py b/gguf-py/scripts/gguf-dump.py
index dbf89150..eeea947f 100755
--- a/gguf-py/scripts/gguf-dump.py
+++ b/gguf-py/scripts/gguf-dump.py
@@ -24,6 +24,56 @@ def get_file_host_endian(reader: GGUFReader) -> tuple[str, str]:
         file_endian = host_endian
     return (host_endian, file_endian)
 
+from tqdm import tqdm
+import gguf.tensor_mapping as tm

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from pathlib import Path
savepath = Path('mm')
savepath.mkdir(exist_ok=True)

import torch
import triton
from triton.ops.matmul import matmul as triton_matmul
#matmul = lambda a,b: _matmul.forward(a,b, acc_dtype=torch.float16, allow_tf32=True, output_dtype=torch.float16) # nightly
matmul = lambda a,b: triton_matmul(a,b, torch.float16) # stable

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import torch
from unsloth import FastLlamaModel
from transformers import TrainingArguments
from datasets import load_dataset
from trl import DPOTrainer

model_name = "teknium/OpenHermes-2.5-Mistral-7B"
model_name = "./OpenHermes-2.5-Mistral-7B"
new_model = "NeuralHermes-2.5-Mistral-7B"

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$ cat OpenHermes-2.5-Mistral-7B/config.json 
{
  "_name_or_path": "mistralai/Mistral-7B-v0.1",
  "architectures": [
    "LlamaForCausalLM"
  ],
  "bos_token_id": 1,
  "eos_token_id": 32000,
  "hidden_act": "silu",
  "hidden_size": 4096,

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''' NOTE:
0. install pandas and numpy to run this
1. Download the data at https://docs.google.com/spreadsheets/d/1QtC8efWw0mVkGXW4QA9bX4f0nJhGbmFqCfVLSumMZ0I/edit **AS A CSV FILE**
2. **REMOVE THE FIRST LINE FROM THE CSV FILE BEFORE RUNNING THIS**
'''


import pandas as pd
import numpy as np
import re

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const tests = ["data:image/jpeg;base64,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# -*- coding: utf-8 -*-
import idaapi
import idautils
import idc
import ida_kernwin

'''SAMPLE INPUT:
0x0000555555557f18│+0x0018: 0x00007ffff7f93500  →  <seccomp_init+0> endbr64
0x0000555555557f20│+0x0020: 0x00007ffff7da0430  →  <__errno_location+0> endbr64
'''

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#!/bin/bash
script=/path/to/RsaCtfTool/RsaCtfTool.py
n=()
c=()
echo 'paste all n:'
for i in `seq 0 2`
do  read
    n[$i]=$REPLY
done
echo 'paste all c:'