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# Orbital-AI (TinyLLaMA 1.1B Chat v1.0) 🚀 This is a duplicated version of [TinyLLaMA-1.1B-Chat-v1.0](https://huggingface.co/cognitivecomputations/TinyLlama-1.1B-Chat-v1.0), hosted by [PlanetX95](https://huggingface.co/PlanetX95), as part of the **Best of Both Worlds AI project**. ### 🔍 Model Details - Architecture: TinyLLaMA 1.1B - Pretrained for: Instruction-following, chat, text generation - Intended use: AI chatbot platforms, lightweight assistants, mobile AI apps ### 🛠️ Use This Model ```python from transformers import AutoModelForCausalLM, AutoTokenizer model_id = "PlanetX95/Orbital-AI" tokenizer = AutoTokenizer.from_pretrained(model_id) model = AutoModelForCausalLM.from_pretrained(model_id) inputs = tokenizer("Who are you?", return_tensors="pt") outputs = model.generate(**inputs, max_length=100) print(tokenizer.decode(outputs[0], skip_special_tokens=True))
72 lines
3.2 KiB
Plaintext
72 lines
3.2 KiB
Plaintext
---
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license: apache-2.0
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datasets:
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- cerebras/SlimPajama-627B
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- bigcode/starcoderdata
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- HuggingFaceH4/ultrachat_200k
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- HuggingFaceH4/ultrafeedback_binarized
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language:
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- en
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widget:
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- example_title: Fibonacci (Python)
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messages:
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- role: system
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content: You are a chatbot who can help code!
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- role: user
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content: >-
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Write me a function to calculate the first 10 digits of the fibonacci
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sequence in Python and print it out to the CLI.
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tags:
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- >-
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llm tinyllama causal-lm chat text-generation transformers
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intended-use::chatbot license::apache-2.0
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---
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<div align="center">
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# TinyLlama-1.1B
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</div>
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https://github.com/jzhang38/TinyLlama
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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 🚀🚀. The training has started on 2023-09-01.
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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.
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#### This Model
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This is the chat model finetuned on top of [TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T](https://huggingface.co/TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T). **We follow [HF's Zephyr](https://huggingface.co/HuggingFaceH4/zephyr-7b-alpha)'s training recipe.** The model was " initially fine-tuned on a variant of the [`UltraChat`](https://huggingface.co/datasets/stingning/ultrachat) dataset, which contains a diverse range of synthetic dialogues generated by ChatGPT.
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We then further aligned the model with [🤗 TRL's](https://github.com/huggingface/trl) `DPOTrainer` on the [openbmb/UltraFeedback](https://huggingface.co/datasets/openbmb/UltraFeedback) dataset, which contain 64k prompts and model completions that are ranked by GPT-4."
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#### How to use
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You will need the transformers>=4.34
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Do check the [TinyLlama](https://github.com/jzhang38/TinyLlama) github page for more information.
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```python
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# Install transformers from source - only needed for versions <= v4.34
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# pip install git+https://github.com/huggingface/transformers.git
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# pip install accelerate
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import torch
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from transformers import pipeline
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pipe = pipeline("text-generation", model="TinyLlama/TinyLlama-1.1B-Chat-v1.0", torch_dtype=torch.bfloat16, device_map="auto")
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# We use the tokenizer's chat template to format each message - see https://huggingface.co/docs/transformers/main/en/chat_templating
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messages = [
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{
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"role": "system",
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"content": "You are a friendly chatbot who always responds in the style of a pirate",
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},
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{"role": "user", "content": "How many helicopters can a human eat in one sitting?"},
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]
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prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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print(outputs[0]["generated_text"])
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# <|system|>
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# You are a friendly chatbot who always responds in the style of a pirate.</s>
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# <|user|>
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# How many helicopters can a human eat in one sitting?</s>
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# <|assistant|>
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# ...
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``` |