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README.md CHANGED
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  ---
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- license: mit
 
 
 
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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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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+ - text: "<|system|>\nYou are a chatbot who can help code!</s>\n<|user|>\nWrite me a function to calculate the first 10 digits of the fibonacci sequence in Python and print it out to the CLI.</s>\n<|assistant|>\n"
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  ---
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+ <div align="center">
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+
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+ # TinyLlama-1.1B
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+ </div>
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+
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+ https://github.com/jzhang38/TinyLlama
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+
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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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+
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+
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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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+
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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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+
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+
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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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+
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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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+
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+ import torch
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+ from transformers import pipeline
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+
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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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+
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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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+ ```
config.json ADDED
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+ {
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+ "architectures": [
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+ "LlamaForCausalLM"
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+ ],
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+ "attention_bias": false,
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+ "bos_token_id": 1,
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+ "eos_token_id": 2,
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+ "hidden_act": "silu",
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+ "hidden_size": 2048,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 5632,
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+ "max_position_embeddings": 2048,
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+ "model_type": "llama",
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+ "num_attention_heads": 32,
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+ "num_hidden_layers": 22,
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+ "num_key_value_heads": 4,
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+ "pretraining_tp": 1,
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+ "rms_norm_eps": 1e-05,
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+ "rope_scaling": null,
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+ "rope_theta": 10000.0,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "bfloat16",
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+ "transformers_version": "4.35.0",
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+ "use_cache": true,
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+ "vocab_size": 32000
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+ }
eval_results.json ADDED
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+ {
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+ "epoch": 3.0,
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+ "eval_runtime": 93.5908,
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+ "eval_samples": 2000,
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+ "eval_samples_per_second": 21.37,
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+ "eval_steps_per_second": 0.673
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+ }
generation_config.json ADDED
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+ {
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+ },
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+ "bos_token": "<s>",
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+ "chat_template": "{% for message in messages %}\n{% if message['role'] == 'user' %}\n{{ '<|user|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'system' %}\n{{ '<|system|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'assistant' %}\n{{ '<|assistant|>\n' + message['content'] + eos_token }}\n{% endif %}\n{% if loop.last and add_generation_prompt %}\n{{ '<|assistant|>' }}\n{% endif %}\n{% endfor %}",
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+ "clean_up_tokenization_spaces": false,
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+ "eos_token": "</s>",
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+ "model_max_length": 2048,
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+ "pad_token": "</s>",
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+ "padding_side": "right",
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+ "sp_model_kwargs": {},
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+ "tokenizer_class": "LlamaTokenizer",
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+ "unk_token": "<unk>",
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+ "use_default_system_prompt": false
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+ }