Codys12

import math
import random
import re
import time
from dataclasses import dataclass
from typing import Any, Dict, List, Optional, Tuple

import numpy as np

Codys12

#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Cross-entropy fine-tune on PrimeIntellect/SYNTHETIC-1
  – ZeRO-2       (no remote_device)
  – Flash-Attn-2 enabled after loading
"""
import argparse, json, os
from pathlib import Path
from typing import Iterable

Codys12

import numpy as np

# ------------------- quantisation helpers (same as user's snippet) -----------
def activation_quant(x):
    scale = 127.0 / np.maximum(np.max(np.abs(x), axis=-1, keepdims=True), 1e-5)
    return np.round(x * scale).clip(-128, 127) / scale

def weight_quant(w):
    scale = 1.0 / np.maximum(np.mean(np.abs(w)), 1e-5)

Codys12

```python
import numpy as np

# ------------------- quantisation helpers (same as user's snippet) -----------
def activation_quant(x):
    scale = 127.0 / np.maximum(np.max(np.abs(x), axis=-1, keepdims=True), 1e-5)
    return np.round(x * scale).clip(-128, 127) / scale

def weight_quant(w):
    scale = 1.0 / np.maximum(np.mean(np.abs(w)), 1e-5)

Codys12

```
pip install git+ https://github.com/childressg/matmulfreellm/tree/master/mmfreelm/ops
```

```
#!/usr/bin/env python
# -*- coding: utf-8 -*-

"""
DeepSpeed ZeRO for memory-efficient training (stage 3).

Codys12

Genhead Agents

Codys12

Example Git Branching Diagram

You can use this diagram as a template to create your own git branching diagrams. Here's how:

1. Create a new diagram with diagrams.net (formerly draw.io)
2. Go to File > Open From > URL
3. Insert this url (it points to the xml data below): https://gist.githubusercontent.com/bryanbraun/8c93e154a93a08794291df1fcdce6918/raw/bf563eb36c3623bb9e7e1faae349c5da802f9fed/template-data.xml
4. Customize as needed for your team.

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