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license: apache-2.0
- cerebras/SlimPajama-627B
- bigcode/starcoderdata
- OpenAssistant/oasst_top1_2023-08-25
- en
<div align="center">
# TinyLlama-1.1B
The TinyLlama project aims to **pretrain** a **1.1B Llama model on 3 trillion tokens**. With some proper optimization, we can achieve this within a span of "just" 90 days using 16 A100-40G GPUs πŸš€πŸš€. The training has started on 2023-09-01.
We adopted exactly the same architecture and tokenizer as Llama 2. This means TinyLlama can be plugged and played in many open-source projects built upon Llama. Besides, TinyLlama is compact with only 1.1B parameters. This compactness allows it to cater to a multitude of applications demanding a restricted computation and memory footprint.
#### This Model
This is the chat model finetuned on top of [TinyLlama/TinyLlama-1.1B-intermediate-step-955k-2T]( **We follow [HF's Zephyr]('s training recipe.** The model was " initially fine-tuned on a variant of the [`UltraChat`]( dataset, which contains a diverse range of synthetic dialogues generated by ChatGPT.
We then further aligned the model with [πŸ€— TRL's]( `DPOTrainer` on the [openbmb/UltraFeedback]( dataset, which contain 64k prompts and model completions that are ranked by GPT-4."
#### How to use
You will need the transformers>=4.34
Do check the [TinyLlama]( github page for more information.
# Install transformers from source - only needed for versions <= v4.34
# pip install git+
# pip install accelerate
import torch
from transformers import pipeline
pipe = pipeline("text-generation", model="TinyLlama/TinyLlama-1.1B-Chat-v0.6", torch_dtype=torch.bfloat16, device_map="auto")
# We use the tokenizer's chat template to format each message - see
messages = [
"role": "system",
"content": "You are a friendly chatbot who always responds in the style of a pirate",
{"role": "user", "content": "How many helicopters can a human eat in one sitting?"},
prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
# <|system|>
# You are a friendly chatbot who always responds in the style of a pirate.</s>
# <|user|>
# How many helicopters can a human eat in one sitting?</s>
# <|assistant|>
# ...