Text Generation
Transformers
ONNX
Safetensors
GGUF
Transformers.js
English
gpt2
humor
parody
tiny
chat
lm-studio
ollama
llama.cpp
gpt
meme
funny
joke
satire
ram
ram-shortage
tiny-model
small-model
micro-model
toy-model
trained-from-scratch
custom-tokenizer
synthetic-data
conversational
chatbot
cpu
low-resource
text-generation-inference
| import random | |
| from pathlib import Path | |
| from vocab import * | |
| OUTPUT_FILE = Path(__file__).resolve().parent.parent / "data" / "ram_altman.txt" | |
| END_TOKEN = "<|i_have_enough_ram|>" | |
| N_SAMPLES = 200_000 | |
| CONVERSATION_CHANCE = 0.15 | |
| MAX_REPLY_WORDS = 170 # pair must fit in the 379 token context | |
| MAX_CONVERSATION_REPLY_WORDS = 70 | |
| def fill(template, word=""): | |
| template = template.replace("{W}", word.upper()) | |
| while "{size}" in template: | |
| template = template.replace("{size}", random.choice(SIZES), 1) | |
| while "{type}" in template: | |
| template = template.replace("{type}", random.choice(TYPES), 1) | |
| return template | |
| def burst(lo, hi): | |
| groups = [RAM, BEGS, SIZES, TYPES, ["MORE"], LORE] | |
| parts = [random.choice(random.choices(groups, weights=[30, 20, 18, 12, 10, 10])[0]) | |
| for _ in range(random.randint(lo, hi))] | |
| if random.random() < 0.85: | |
| parts.append(random.choice(RAM)) | |
| return " ".join(parts) | |
| def sentences(lo, hi): | |
| out = fill(random.choice(SENTENCES)) | |
| for _ in range(random.randint(lo, hi) - 1): | |
| out += random.choice(SEPARATORS) + fill(random.choice(SENTENCES)) | |
| return out | |
| def spam(): | |
| return " ".join([random.choice(SPAM_WORDS)] * random.randint(10, 30)) | |
| def rant(lo, hi): | |
| chunks = [] | |
| for _ in range(random.randint(lo, hi)): | |
| r = random.random() | |
| chunks.append(sentences(1, 3) if r < 0.45 else burst(5, 12) if r < 0.85 else spam()) | |
| return random.choice(SEPARATORS).join(chunks) | |
| def tail(size): | |
| if size == "short": | |
| return random.choice(["", burst(1, 4)]) | |
| if size == "normal": | |
| return random.choice([sentences(1, 3), burst(4, 10)]) | |
| if size == "medium": | |
| return random.choice([sentences(3, 5), burst(10, 20), rant(2, 3)]) | |
| return rant(7, 12) # Giant | |
| def reply_size(user, rant=False): | |
| # longer messages tend to get longer replies; unknown topics get the rant | |
| # tuned so the reply length median lands around 15 words | |
| n = len(user.split()) | |
| if rant: | |
| weights = [28, 50, 16, 6] if n <= 9 else [22, 50, 20, 8] | |
| else: | |
| weights = [48, 40, 10, 2] if n <= 3 else [43, 44, 11, 2] if n <= 9 else [33, 45, 16, 6] | |
| return random.choices(["short", "normal", "medium", "giant"], weights)[0] | |
| def join(reply, rest): | |
| if not rest: | |
| return reply | |
| return reply + (" " if not reply[-1].isalnum() else random.choice(SEPARATORS)) + rest | |
| def finish(reply, max_words=MAX_REPLY_WORDS): | |
| reply = " ".join(reply.split()[:max_words]) | |
| if random.random() < 0.01: | |
| reply = join(reply, FALSE_ENDING) | |
| if reply[-1].isalnum(): | |
| reply += random.choice(ENDINGS) | |
| return reply | |
| # user text | |
| def style(line): | |
| r = random.random() | |
| line = line[0].upper() + line[1:] if r < 0.45 else line.upper() if r < 0.55 else line.lower() | |
| if line[-1].isalnum() and random.random() < 0.5: | |
| line += random.choice(USER_PUNCTUATION) | |
| return line | |
| def lengthen(line): | |
| if random.random() < 0.25: | |
| line = line.rstrip("?!.") + ". " + ". ".join(random.sample(FILLERS, random.randint(1, 3))) | |
| return line | |
| def pluralize(word): | |
| if word.endswith("s"): # news, chess, tennis, bus... | |
| return word | |
| if word.endswith("y") and word[-2] not in "aeiou": | |
| return word[:-1] + "ies" | |
| if word.endswith(("x", "ch", "sh", "o")): | |
| return word + "es" | |
| return word + "s" | |
| def random_noun(): | |
| word = random.choice(NOUNS) | |
| return pluralize(word) if random.random() < 0.4 else word | |
| def topic_word(): | |
| return random.choice(random.choice(list(TOPICS.values()))["words"]) | |
| def topic_pair(): | |
| topic = random.choice(list(TOPICS.values())) | |
| word = random.choice(topic["words"]) | |
| hook = random.choice(ECHO_HOOKS if random.random() < 0.25 else topic["hooks"]) | |
| return lengthen(random.choice(TOPIC_TEMPLATES).format(w=word)), hook, word | |
| def noun_pair(): | |
| user = lengthen(random.choice(TOPIC_TEMPLATES).format(w=random_noun())) | |
| return user, random.choice(DISMISS_HOOKS), None | |
| def reaction_pair(): | |
| messages, replies = random.choice(list(REACTIONS.values())) | |
| return random.choice(messages), random.choice(replies), None | |
| def math_pair(): | |
| a, b = random.randint(0, 9), random.randint(0, 9) | |
| if random.random() < 0.5: | |
| user = random.choice(MATH_DIGITS).format(a=a, b=b) | |
| else: | |
| user = random.choice(MATH_WORDS).format(a=NUMBERS[a], b=NUMBERS[b]) | |
| return user, random.choice(MATH_REPLIES).replace("{s}", str(a + b)), None | |
| def ram_pair(): | |
| n = random.choice(SIZES) | |
| user = random.choice(RAM_AMOUNT_USER).format(n=n) | |
| reply = random.choice(RAM_AMOUNT_REPLIES).replace("{n}", n) | |
| return user, reply, None | |
| def generic_pair(): | |
| if random.random() < 0.5: | |
| user = random.choice(GENERIC_QUESTIONS) | |
| else: | |
| user = random.choice(TOPIC_TEMPLATES).format(w=random.choice(GENERIC_WORDS)) | |
| return lengthen(user), random.choice(SENTENCES), None | |
| def first_message(kinds, weights): | |
| user, hook, word = random.choices(kinds, weights)[0]() | |
| return style(user), fill(hook, word or ""), word | |
| def single_pair(): | |
| kinds = [topic_pair, noun_pair, reaction_pair, math_pair, generic_pair, ram_pair] | |
| weights = [28, 12, 25, 8, 12, 15] | |
| kind = random.choices(kinds, weights)[0] | |
| user, reply, word = kind() | |
| rant = kind in (noun_pair, generic_pair, ram_pair) | |
| return style(user), finish(join(fill(reply, word or ""), tail(reply_size(user, rant=rant)))) | |
| def conversation(): | |
| # remembers what the user said, still only wants RAM and asks for more | |
| level = random.randint(1, 8) | |
| user, reply, _ = first_message([topic_pair, noun_pair, reaction_pair, ram_pair], [40, 30, 15, 15]) | |
| reply += ("." if reply[-1].isalnum() else "") + f" I NEED {SIZES[level]}" | |
| turns = [(user, finish(join(reply, tail("normal")), MAX_CONVERSATION_REPLY_WORDS))] | |
| for _ in range(random.randint(1, 3)): | |
| prev = SIZES[level] | |
| level = min(level + random.randint(1, 3), len(SIZES) - 1) | |
| size = SIZES[level] if level < len(SIZES) - 1 else FINAL_OFFER | |
| if random.random() < 0.8: # "and X?" | |
| echo = random.random() < 0.5 # topic words are echoed, anything else ignored | |
| word = topic_word() if echo else random_noun() | |
| user = style(random.choice(FOLLOW_UPS_WORD).format(w=word)) | |
| replies = FOLLOW_UP_ECHO_REPLIES if echo else FOLLOW_UP_DISMISS_REPLIES | |
| reply = fill(random.choice(replies).replace("{esc}", size), word) | |
| else: # "why?", "ok", "stop" | |
| messages, replies = random.choice(list(FOLLOW_UPS_PLAIN.values())) | |
| user = style(random.choice(messages)) | |
| reply = fill(random.choice(replies).replace("{esc}", size).replace("{prev}", prev)) | |
| rest = tail(random.choice(["short", "normal", "medium", "medium"])) | |
| turns.append((user, finish(join(reply, rest), MAX_CONVERSATION_REPLY_WORDS))) | |
| return turns | |
| if __name__ == "__main__": | |
| random.seed(42) | |
| n_pairs = 0 | |
| with open(OUTPUT_FILE, "w", encoding="utf-8") as f: | |
| for _ in range(N_SAMPLES): | |
| turns = conversation() if random.random() < CONVERSATION_CHANCE else [single_pair()] | |
| for user, reply in turns: | |
| f.write(f"User: {user}\nRAM-ALTMAN: {reply}{END_TOKEN}\n") | |
| n_pairs += len(turns) | |
| print(f"{OUTPUT_FILE.name}: {N_SAMPLES:,} samples, {n_pairs:,} pairs") | |