diff --git a/.gitignore b/.gitignore
index 15201ac..a480c19 100644
--- a/.gitignore
+++ b/.gitignore
@@ -169,3 +169,4 @@ cython_debug/
# PyPI configuration file
.pypirc
+/dataset_cache.bin
\ No newline at end of file
diff --git a/config.py b/config.py
new file mode 100644
index 0000000..1f31c4d
--- /dev/null
+++ b/config.py
@@ -0,0 +1,19 @@
+import os
+import torch
+from dotenv import load_dotenv
+
+load_dotenv()
+
+
+class Config:
+ model_dim = int(os.getenv("MODEL_DIM", 256))
+ num_layers = int(os.getenv("NUM_LAYERS", 4))
+ num_heads = int(os.getenv("HEADS", 8))
+ vocab_size = int(os.getenv("VOCAB_SIZE", 30000))
+ context_size = int(os.getenv("CONTEXT_SIZE", 512))
+ batch_size = int(os.getenv("BATCH_SIZE", 8))
+ lr = float(os.getenv("LEARNING_RATE", 1e-4))
+ device = "cuda" if torch.cuda.is_available() else "cpu"
+
+
+cfg = Config()
diff --git a/main.py b/main.py
deleted file mode 100644
index 70d26b7..0000000
--- a/main.py
+++ /dev/null
@@ -1,70 +0,0 @@
-import discord
-import requests
-import json
-import os
-from dotenv import load_dotenv
-
-# Load environment variables from .env file
-load_dotenv()
-
-# Replace with your bot token
-BOT_TOKEN = os.getenv('DISCORD_TOKEN')
-
-# Ollama configuration
-OLLAMA_API_URL = 'http://192.168.1.159:11434/api/generate' # Adjust if your Ollama setup is different
-
-# Set up the Discord client
-intents = discord.Intents.default()
-intents.messages = True
-intents.message_content = True
-
-client = discord.Client(intents=intents)
-
-
-# Function to query Ollama
-def query_ollama(prompt):
- payload = {
- "prompt": prompt,
- "model": "nollama/mythomax-l2-13b:Q4_K_M" # Replace with your Ollama model
- }
- try:
- response = requests.post(OLLAMA_API_URL, json=payload, stream=True)
- if response.status_code == 200:
- collected_response = ""
- # Stream and parse each line of JSON from the response
- for line in response.iter_lines(decode_unicode=True):
- if line.strip(): # Skip empty lines
- try:
- data = json.loads(line) # Parse each line as JSON
- collected_response += data.get("response", "")
- if data.get("done", False):
- break
- except json.JSONDecodeError as e:
- print(f"Error decoding JSON line: {line}, Error: {e}")
- return collected_response.strip() or "No response from model."
- else:
- return f"Error: {response.status_code} - {response.text}"
- except requests.RequestException as e:
- return f"Error connecting to Ollama: {str(e)}"
-
-
-# Event for when the bot is ready
-@client.event
-async def on_ready():
- print(f'We have logged in as {client.user}')
-
-
-# Event for when a message is sent
-@client.event
-async def on_message(message):
- # Ignore the bot's own messages
- if message.author == client.user:
- return
-
- # Respond to all messages except those in DMs
- if not isinstance(message.channel, discord.DMChannel):
- response = query_ollama(message.content.strip())
- await message.channel.send(response)
-
-# Run the bot
-client.run(BOT_TOKEN)
diff --git a/tokenizer.json b/tokenizer.json
new file mode 100644
index 0000000..0923e5e
--- /dev/null
+++ b/tokenizer.json
@@ -0,0 +1,107920 @@
+{
+ "version": "1.0",
+ "truncation": null,
+ "padding": null,
+ "added_tokens": [
+ {
+ "id": 0,
+ "content": "[PAD]",
+ "single_word": false,
+ "lstrip": false,
+ "rstrip": false,
+ "normalized": false,
+ "special": true
+ },
+ {
+ "id": 1,
+ "content": "[UNK]",
+ "single_word": false,
+ "lstrip": false,
+ "rstrip": false,
+ "normalized": false,
+ "special": true
+ }
+ ],
+ "normalizer": null,
+ "pre_tokenizer": null,
+ "post_processor": null,
+ "decoder": {
+ "type": "ByteLevel",
+ "add_prefix_space": true,
+ "trim_offsets": true,
+ "use_regex": true
+ },
+ "model": {
+ "type": "BPE",
+ "dropout": null,
+ "unk_token": "[UNK]",
+ "continuing_subword_prefix": null,
+ "end_of_word_suffix": null,
+ "fuse_unk": false,
+ "byte_fallback": false,
+ "ignore_merges": false,
+ "vocab": {
+ "[PAD]": 0,
+ "[UNK]": 1,
+ "!": 2,
+ "\"": 3,
+ "#": 4,
+ "$": 5,
+ "%": 6,
+ "&": 7,
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+ "series,": 18954,
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+ "Init",
+ "ial"
+ ],
+ [
+ "obst",
+ "acles"
+ ],
+ [
+ "Partners",
+ "hip"
+ ],
+ [
+ "S",
+ "omet"
+ ],
+ [
+ "m",
+ "old"
+ ],
+ [
+ "not",
+ "es."
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+ [
+ "ah",
+ "an"
+ ],
+ [
+ "pris",
+ "on,"
+ ],
+ [
+ "Arn",
+ "old"
+ ],
+ [
+ "popu",
+ "list"
+ ],
+ [
+ "In",
+ "clud"
+ ],
+ [
+ "Em",
+ "ir"
+ ],
+ [
+ "enjoy",
+ "s"
+ ],
+ [
+ "achieve",
+ "ments"
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+ [
+ "accompany",
+ "ing"
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+ [
+ "Hundred",
+ "s"
+ ],
+ [
+ "“",
+ "and"
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+ [
+ "happ",
+ "ily"
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+ [
+ "successful",
+ "."
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+ [
+ "catch",
+ "es"
+ ],
+ [
+ "jer",
+ "sey"
+ ],
+ [
+ "c",
+ "attle"
+ ],
+ [
+ "ack",
+ "ed"
+ ],
+ [
+ "un",
+ "popular"
+ ],
+ [
+ "ab",
+ "usive"
+ ],
+ [
+ "new",
+ "com"
+ ],
+ [
+ "__",
+ "_"
+ ],
+ [
+ "camer",
+ "a,"
+ ],
+ [
+ "strateg",
+ "y,"
+ ],
+ [
+ "S",
+ "V"
+ ],
+ [
+ "port",
+ "able"
+ ],
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+ "j",
+ "pg"
+ ],
+ [
+ "late",
+ ","
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+ "prison",
+ "er"
+ ],
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+ "ch",
+ "uck"
+ ],
+ [
+ "stor",
+ "ms"
+ ],
+ [
+ "bound",
+ "ary"
+ ],
+ [
+ "dis",
+ "orders"
+ ],
+ [
+ "fl",
+ "own"
+ ],
+ [
+ "candid",
+ "ate."
+ ],
+ [
+ "plant",
+ "s,"
+ ],
+ [
+ "entertain",
+ "ing"
+ ],
+ [
+ "gl",
+ "ac"
+ ],
+ [
+ "cir",
+ "cular"
+ ],
+ [
+ "victim",
+ "s."
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+ [
+ "goog",
+ "le"
+ ],
+ [
+ "$",
+ "14"
+ ],
+ [
+ "JS",
+ "ON"
+ ],
+ [
+ "S",
+ "kill"
+ ],
+ [
+ "iz",
+ "able"
+ ],
+ [
+ "ah",
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+ ],
+ [
+ "position",
+ "s."
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+ [
+ "pract",
+ "iced"
+ ],
+ [
+ "Gu",
+ "ant"
+ ],
+ [
+ "lower",
+ "ing"
+ ],
+ [
+ "M",
+ "T"
+ ],
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+ "De",
+ "ut"
+ ],
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+ "199",
+ "8,"
+ ],
+ [
+ "Irel",
+ "and,"
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+ [
+ "########",
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+ [
+ "(",
+ "CNN"
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+ [
+ "/",
+ "*"
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+ "who",
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+ "cept"
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+ "D",
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+ "H",
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+ "L",
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+ "h",
+ "og"
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+ "Ad",
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+ "Consider",
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+ "C",
+ "lem"
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+ "L",
+ "ith"
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+ "m",
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+ [
+ "over",
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+ [
+ "Paul",
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+ [
+ "church",
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+ "Bush",
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+ "RELATED",
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+ "contin",
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+ [
+ "pay",
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+ "form",
+ "ul"
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+ [
+ "Pl",
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+ "Trans",
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+ "chart",
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+ "uplo",
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+ "ap",
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+ ],
+ [
+ "17",
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+ "happen",
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+ [
+ "vo",
+ "ice."
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+ [
+ "OS",
+ "E"
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+ [
+ "mother",
+ "."
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+ "wound",
+ "s"
+ ],
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+ "R",
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+ "pre",
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+ "oc",
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+ [
+ "three",
+ ","
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+ [
+ "conf",
+ "isc"
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+ [
+ "$100",
+ ",000"
+ ],
+ [
+ "alumin",
+ "um"
+ ],
+ [
+ "O",
+ "W"
+ ],
+ [
+ "d",
+ "les"
+ ],
+ [
+ "part",
+ "ner,"
+ ],
+ [
+ "Play",
+ "ing"
+ ],
+ [
+ "batt",
+ "ing"
+ ],
+ [
+ "Depart",
+ "ment."
+ ],
+ [
+ "J",
+ "aze"
+ ],
+ [
+ "ist",
+ "ically"
+ ],
+ [
+ "beginning",
+ ","
+ ],
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+ "convers",
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+ [
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+ "homore"
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+ "Wi-",
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+ "light",
+ "ly"
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+ [
+ "13",
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+ [
+ "price",
+ ","
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+ [
+ "upgrad",
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+ "aver",
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+ [
+ "Add",
+ "ing"
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+ [
+ "Ukrain",
+ "e,"
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+ [
+ "sovereign",
+ "ty"
+ ],
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+ "emphas",
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+ [
+ "7",
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+ [
+ "S",
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+ ],
+ [
+ "US",
+ "C"
+ ],
+ [
+ "t",
+ "ide"
+ ],
+ [
+ "so",
+ "ap"
+ ],
+ [
+ "opportun",
+ "ity."
+ ],
+ [
+ "effort",
+ "s,"
+ ],
+ [
+ "UT",
+ "C"
+ ],
+ [
+ "entrepre",
+ "neurs"
+ ],
+ [
+ "molecul",
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+ ],
+ [
+ "200",
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+ [
+ "break",
+ "."
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+ [
+ "bo",
+ "ots"
+ ],
+ [
+ "wast",
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+ [
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+ "so"
+ ],
+ [
+ "For",
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+ ],
+ [
+ "pun",
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+ "respons",
+ "ive"
+ ],
+ [
+ "$",
+ "400"
+ ],
+ [
+ "v",
+ "ak"
+ ],
+ [
+ "over",
+ "view"
+ ],
+ [
+ "administ",
+ "ered"
+ ],
+ [
+ "Def",
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+ ],
+ [
+ "tw",
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+ ],
+ [
+ "Ar",
+ "c"
+ ],
+ [
+ "hi",
+ "ke"
+ ],
+ [
+ "gr",
+ "a"
+ ],
+ [
+ "test",
+ "s,"
+ ],
+ [
+ "bul",
+ "lets"
+ ],
+ [
+ "Sg",
+ "t."
+ ],
+ [
+ "h",
+ "it."
+ ],
+ [
+ "perform",
+ "s"
+ ],
+ [
+ "K",
+ "enny"
+ ],
+ [
+ "g",
+ "io"
+ ],
+ [
+ "he",
+ "el"
+ ],
+ [
+ "incl",
+ "ined"
+ ],
+ [
+ "Nor",
+ "m"
+ ],
+ [
+ "Hon",
+ "or"
+ ],
+ [
+ "T",
+ "iger"
+ ],
+ [
+ "g",
+ "mail"
+ ],
+ [
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+ "dark",
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+ ],
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+ "C",
+ "um"
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+ "M",
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+ ],
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+ "4",
+ "50"
+ ],
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+ "M",
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+ ],
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+ "fact",
+ "ories"
+ ],
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+ "foreign",
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+ ],
+ [
+ "Leg",
+ "acy"
+ ],
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+ "cal",
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+ ],
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+ "18",
+ "00"
+ ],
+ [
+ "23",
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+ ],
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+ "tool",
+ "s,"
+ ],
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+ "in-",
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+ ],
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+ "any",
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+ ],
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+ "Ar",
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+ ],
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+ "universe",
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+ ],
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+ "1",
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+ ],
+ [
+ "S",
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+ ],
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+ "un",
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+ ],
+ [
+ "under",
+ "way"
+ ],
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+ "200",
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+ "whe",
+ "at"
+ ],
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+ "vehic",
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+ "aw",
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+ ],
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+ "pressure",
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+ ],
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+ "Internet",
+ "."
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+ "O",
+ "m"
+ ],
+ [
+ "2.",
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+ "'",
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+ ],
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+ "B",
+ "od"
+ ],
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+ "believe",
+ ","
+ ],
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+ "camer",
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+ "-",
+ "hop"
+ ],
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+ "C",
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+ ],
+ [
+ "re",
+ "nov"
+ ],
+ [
+ "protest",
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+ ],
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+ "inher",
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+ ],
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+ "-",
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+ ],
+ [
+ "s",
+ "worn"
+ ],
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+ "Su",
+ "z"
+ ],
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+ ],
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+ "Spain",
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+ ],
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+ "Inc",
+ ".,"
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+ "e",
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+ ],
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+ ],
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+ "fail",
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+ "track",
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+ ],
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+ "gas",
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+ ],
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+ "material",
+ ","
+ ],
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+ "appeal",
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+ "Scient",
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+ "U",
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+ [
+ "g",
+ "ithub"
+ ],
+ [
+ "st",
+ "unt"
+ ],
+ [
+ "om",
+ "on"
+ ],
+ [
+ "V",
+ "ia"
+ ],
+ [
+ "fin",
+ "ally,"
+ ],
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+ "discover",
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+ ],
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+ "Greg",
+ "ory"
+ ],
+ [
+ "R",
+ "ho"
+ ],
+ [
+ "and",
+ "o"
+ ],
+ [
+ "Ow",
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+ ],
+ [
+ "alloc",
+ "ated"
+ ],
+ [
+ "Hezbol",
+ "lah"
+ ],
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+ "R",
+ "um"
+ ],
+ [
+ "b",
+ "il"
+ ],
+ [
+ "“",
+ "Some"
+ ],
+ [
+ "at",
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+ ],
+ [
+ "Cam",
+ "bod"
+ ],
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+ "ub",
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+ ],
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+ "pat",
+ "ience"
+ ],
+ [
+ "repe",
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+ ],
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+ "constitut",
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+ ],
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+ "M",
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+ ],
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+ "y",
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+ "comp",
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+ ],
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+ "dis",
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+ ],
+ [
+ "come",
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+ ],
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+ "return",
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+ ],
+ [
+ "pris",
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+ ],
+ [
+ "complex",
+ ","
+ ],
+ [
+ "cool",
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+ ],
+ [
+ "!!!!!!!!",
+ "!!!!!!!!"
+ ],
+ [
+ "8",
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+ ],
+ [
+ ".[",
+ "4"
+ ],
+ [
+ "Red",
+ "skins"
+ ],
+ [
+ "February",
+ "."
+ ],
+ [
+ "B",
+ "is"
+ ],
+ [
+ "crim",
+ "es."
+ ],
+ [
+ "uk",
+ "i"
+ ],
+ [
+ "opt",
+ "ion,"
+ ],
+ [
+ "right",
+ ")"
+ ],
+ [
+ "trans",
+ "fers"
+ ],
+ [
+ "2.",
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+ ],
+ [
+ "ling",
+ "ton"
+ ],
+ [
+ "lock",
+ "s"
+ ],
+ [
+ "document",
+ "s."
+ ],
+ [
+ "Alz",
+ "heim"
+ ],
+ [
+ "make",
+ "up"
+ ],
+ [
+ "pack",
+ "aging"
+ ],
+ [
+ "conce",
+ "aled"
+ ],
+ [
+ "Mir",
+ "ror"
+ ],
+ [
+ "(",
+ "left"
+ ],
+ [
+ "D",
+ "ot"
+ ],
+ [
+ "r",
+ "ation."
+ ],
+ [
+ "forum",
+ "s"
+ ],
+ [
+ "veget",
+ "ables"
+ ],
+ [
+ "M",
+ "AT"
+ ],
+ [
+ "br",
+ "ag"
+ ],
+ [
+ "Dr",
+ "af"
+ ],
+ [
+ "football",
+ ","
+ ],
+ [
+ "(",
+ "Image:"
+ ],
+ [
+ "way",
+ ":"
+ ],
+ [
+ "them",
+ ".\""
+ ],
+ [
+ "No",
+ "va"
+ ],
+ [
+ "milit",
+ "ar"
+ ],
+ [
+ "fre",
+ "ed"
+ ],
+ [
+ "Dis",
+ "covery"
+ ],
+ [
+ "out",
+ "look"
+ ],
+ [
+ "cas",
+ "ino"
+ ],
+ [
+ "Whats",
+ "App"
+ ],
+ [
+ ":",
+ ")"
+ ],
+ [
+ "“",
+ "Do"
+ ],
+ [
+ "Ad",
+ "venture"
+ ],
+ [
+ "Sch",
+ "ult"
+ ],
+ [
+ "internet",
+ "."
+ ],
+ [
+ "maxim",
+ "ize"
+ ],
+ [
+ "compat",
+ "ibility"
+ ],
+ [
+ "feas",
+ "ible"
+ ],
+ [
+ "w",
+ "anna"
+ ],
+ [
+ "make",
+ "."
+ ],
+ [
+ "Rock",
+ "et"
+ ],
+ [
+ "Sho",
+ "ck"
+ ],
+ [
+ "ste",
+ "ering"
+ ],
+ [
+ "boast",
+ "s"
+ ],
+ [
+ "с",
+ "т"
+ ],
+ [
+ "po",
+ "ised"
+ ],
+ [
+ "In",
+ "spe"
+ ],
+ [
+ "mar",
+ "sh"
+ ],
+ [
+ "E",
+ "volution"
+ ],
+ [
+ "G",
+ "RE"
+ ],
+ [
+ "in",
+ "test"
+ ],
+ [
+ "ol",
+ "ig"
+ ],
+ [
+ "hair",
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+ "Sub",
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+ ],
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+ "Fam",
+ "il"
+ ],
+ [
+ "N",
+ "an"
+ ],
+ [
+ "ot",
+ "er"
+ ],
+ [
+ "Hero",
+ "es"
+ ],
+ [
+ "(c",
+ ")"
+ ],
+ [
+ "G",
+ "ut"
+ ],
+ [
+ "sh",
+ "i"
+ ],
+ [
+ "ning",
+ "s"
+ ],
+ [
+ "partic",
+ "le"
+ ],
+ [
+ "president",
+ "'s"
+ ],
+ [
+ "kind",
+ "a"
+ ],
+ [
+ "app",
+ "arat"
+ ],
+ [
+ "bre",
+ "wing"
+ ],
+ [
+ "zomb",
+ "ie"
+ ],
+ [
+ "ro",
+ "pe"
+ ],
+ [
+ "dis",
+ "placed"
+ ],
+ [
+ "US",
+ "E"
+ ],
+ [
+ "ecolog",
+ "ical"
+ ],
+ [
+ "ific",
+ "ation,"
+ ],
+ [
+ "greet",
+ "ed"
+ ],
+ [
+ "s",
+ "way"
+ ],
+ [
+ "deb",
+ "t,"
+ ],
+ [
+ "hom",
+ "ophob"
+ ],
+ [
+ "Google",
+ "+"
+ ],
+ [
+ "request",
+ "."
+ ],
+ [
+ "Church",
+ ","
+ ],
+ [
+ "Mun",
+ "ich"
+ ],
+ [
+ "pon",
+ "der"
+ ],
+ [
+ "oper",
+ "ative"
+ ],
+ [
+ "$1",
+ ",000"
+ ],
+ [
+ "ine",
+ "ff"
+ ],
+ [
+ "ang",
+ "les"
+ ],
+ [
+ "record",
+ "ings"
+ ],
+ [
+ "ium",
+ "."
+ ],
+ [
+ "Glas",
+ "g"
+ ],
+ [
+ "_",
+ "t"
+ ],
+ [
+ "ro",
+ ","
+ ],
+ [
+ "am",
+ "bers"
+ ],
+ [
+ "ver",
+ "ified"
+ ],
+ [
+ "sk",
+ "i,"
+ ],
+ [
+ "log",
+ "ging"
+ ],
+ [
+ "Fran",
+ "co"
+ ]
+ ]
+ }
+}
\ No newline at end of file
diff --git a/train.py b/train.py
new file mode 100644
index 0000000..a5d1bea
--- /dev/null
+++ b/train.py
@@ -0,0 +1,159 @@
+import torch
+import torch.nn as nn
+import time
+import os
+import numpy as np
+from torch.utils.data import Dataset, DataLoader
+from datasets import load_dataset
+from tokenizers import Tokenizer, models, trainers, decoders
+from config import cfg
+from torch.cuda.amp import autocast, GradScaler
+
+
+# 1. Tokenizer Implementation (Modified)
+class RubyTokenizer:
+ def __init__(self):
+ self.tokenizer = Tokenizer(models.BPE(unk_token="[UNK]"))
+ self.tokenizer.add_special_tokens(["[PAD]", "[UNK]"])
+ self.tokenizer.decoder = decoders.ByteLevel()
+
+ def train(self, texts):
+ trainer = trainers.BpeTrainer(
+ special_tokens=["[PAD]", "[UNK]"],
+ vocab_size=cfg.vocab_size,
+ min_frequency=2, # Modified
+ show_progress=True
+ )
+ self.tokenizer.train_from_iterator(
+ (text.split() for text in texts), # Modified: better word handling
+ trainer=trainer
+ )
+
+ def encode(self, text):
+ return self.tokenizer.encode(text).ids
+
+ @property
+ def pad_id(self):
+ return self.tokenizer.token_to_id("[PAD]") # Modified
+
+
+# 2. Optimized Dataset (Modified padding handling)
+class CachedDataset(Dataset):
+ def __init__(self):
+ self.data = np.memmap("dataset_cache.bin",
+ dtype=np.int32,
+ mode="r",
+ shape=(os.path.getsize("dataset_cache.bin")//4,))
+
+ def __len__(self):
+ return len(self.data) // cfg.context_size
+
+ def __getitem__(self, idx):
+ start = idx * cfg.context_size
+ return torch.from_numpy(self.data[start:start+cfg.context_size].copy())
+
+
+# 3. Transformer Model (Modified padding_idx)
+class Transformer(nn.Module):
+ def __init__(self, pad_id):
+ super().__init__()
+ self.embed = nn.Embedding(
+ cfg.vocab_size,
+ cfg.model_dim,
+ padding_idx=pad_id # Modified
+ )
+ self.blocks = nn.ModuleList([
+ nn.TransformerEncoderLayer(
+ d_model=cfg.model_dim,
+ nhead=cfg.num_heads,
+ dim_feedforward=cfg.model_dim*4,
+ batch_first=True
+ ) for _ in range(cfg.num_layers)
+ ])
+ self.head = nn.Linear(cfg.model_dim, cfg.vocab_size)
+
+ def forward(self, x):
+ x = self.embed(x)
+ for block in self.blocks:
+ x = block(x)
+ return self.head(x)
+
+
+# 4. Main Training Process (Critical fixes)
+def main():
+ # Initialize tokenizer
+ tokenizer = RubyTokenizer()
+
+ if not os.path.exists("dataset_cache.bin"):
+ print("Creating dataset cache...")
+ ds = load_dataset("openwebtext", split="train[:5%]")
+
+ # Train and save tokenizer (Modified)
+ if not os.path.exists("tokenizer.json"):
+ print("Training tokenizer...")
+ tokenizer.train([text for text in ds["text"] if len(text) > 100])
+ tokenizer.tokenizer.save("tokenizer.json")
+ else:
+ tokenizer.tokenizer = Tokenizer.from_file("tokenizer.json")
+
+ # Tokenize and cache data (Modified)
+ all_tokens = []
+ pad_id = tokenizer.pad_id
+
+ for text in ds["text"]:
+ tokens = tokenizer.encode(text)
+ tokens = tokens[:cfg.context_size] # Truncate after tokenization
+ pad_len = cfg.context_size - len(tokens)
+ all_tokens.extend(tokens + [pad_id]*pad_len) # Modified
+
+ memmap = np.memmap("dataset_cache.bin",
+ dtype=np.int32,
+ mode="w+",
+ shape=(len(all_tokens),))
+ memmap[:] = np.array(all_tokens, dtype=np.int32)
+ del memmap
+
+ # Test tokenizer (Modified)
+ test_text = "The quick brown fox jumps over the lazy dog."
+ print("Tokenizer test:", tokenizer.tokenizer.encode(test_text).tokens)
+
+ # Initialize model with pad_id (Modified)
+ model = Transformer(pad_id=tokenizer.pad_id).to(cfg.device)
+ opt = torch.optim.AdamW(model.parameters(), lr=cfg.lr)
+ scaler = GradScaler()
+
+ dataset = CachedDataset()
+ loader = DataLoader(dataset,
+ batch_size=cfg.batch_size,
+ pin_memory=True,
+ shuffle=True)
+
+ # Training loop (Modified loss calculation)
+ start = time.time()
+ for step, batch in enumerate(loader):
+ batch = batch.to(cfg.device, non_blocking=True)
+
+ inputs = batch[:, :-1]
+ targets = batch[:, 1:]
+
+ with autocast():
+ outputs = model(inputs)
+ loss = torch.nn.functional.cross_entropy(
+ outputs.reshape(-1, cfg.vocab_size),
+ targets.reshape(-1).long(),
+ ignore_index=tokenizer.pad_id # Modified
+ )
+
+ scaler.scale(loss).backward()
+ scaler.step(opt)
+ scaler.update()
+ opt.zero_grad()
+
+ if step % 10 == 0:
+ elapsed = time.time() - start
+ speed = (step + 1) * cfg.batch_size / elapsed
+ print(f"Step {step} | Loss: {loss.item():.4f} | Speed: {speed:.1f} samples/s")
+
+
+if __name__ == "__main__":
+ main()