Datasets:
File size: 2,469 Bytes
71f8f13 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 | import json
import struct
import numpy as np
import random
import os
print("🛠️ Krynex 200K Parameters Testing")
print("="*40)
dataset_path = "/storage/emulated/0/Download/dataset.jsonl"
if not os.path.exists(dataset_path):
dataset_path = "dataset.jsonl"
text_data = []
with open(dataset_path, "r", encoding="utf-8") as f:
for line in f:
data = json.loads(line)
text_data.append(data.get("instruction", "") + " " + data.get("output", ""))
full_text = " ".join(text_data)
words = sorted(list(set(full_text.lower().split())))
t2i = {w: i for i, w in enumerate(words)}
i2t = {i: w for i, w in enumerate(words)}
vocab_size = len(t2i)
hidden_size = 64
tflite_path = "full_dataset_model.tflite"
if not os.path.exists(tflite_path):
tflite_path = f"/storage/emulated/0/Download/{tflite_path}"
with open(tflite_path, "rb") as f:
magic, offset = struct.unpack('<4sI', f.read(8))
l1 = struct.unpack('<I', f.read(4))[0]
W1 = np.frombuffer(f.read(l1), dtype=np.float32).reshape((hidden_size, vocab_size))
l2 = struct.unpack('<I', f.read(4))[0]
W2 = np.frombuffer(f.read(l2), dtype=np.float32).reshape((vocab_size, hidden_size))
b1 = np.zeros((hidden_size, 1), dtype=np.float32)
b2 = np.zeros((vocab_size, 1), dtype=np.float32)
seq_length = 12
def softmax(x):
e = np.exp(x - np.max(x))
return e / (e.sum() + 1e-8)
def gen(seed="hello", length=15):
words_list = seed.lower().split()
if not words_list:
words_list = ["hello"]
res = words_list.copy()
for _ in range(length):
ctx = res[-seq_length:] if len(res) >= seq_length else res
ctx = ctx + [" "] * (seq_length - len(ctx))
idx = [t2i.get(w, 0) for w in ctx]
X = np.zeros((vocab_size, seq_length))
X[idx, np.arange(seq_length)] = 1
h = np.tanh(W1 @ X + b1)
y_pred = softmax(W2 @ h + b2)
probs = y_pred[:, -1].flatten()
probs = probs / (np.sum(probs) + 1e-12)
probs = np.clip(probs, 0, 1)
probs = probs / (np.sum(probs) + 1e-12)
next_idx = np.random.choice(vocab_size, p=probs)
res.append(i2t.get(next_idx, "<unk>"))
return " ".join(res)
print("💬 Chat ('exit' - stop)")
while True:
u = input("\n👤 You: ").strip()
if u.lower() in ['выход', 'exit', 'stop', 'стоп']:
print("🤖 Goodbye!")
break
if u:
print(f"\n🤖 AI: {gen(u, 15)}") |