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TinyLlama-1.1B-Chat-v1.0-GGUF

Text Generation
Transformers
GGUF
English
llama
GGUF
conversational
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  1. README.md +16 -2
  2. TinyLlama-1.1B-Chat-v1.0-Q2_K.gguf +2 -2
  3. TinyLlama-1.1B-Chat-v1.0-Q3_K.gguf +2 -2
  4. TinyLlama-1.1B-Chat-v1.0-Q3_K_L.gguf +2 -2
  5. TinyLlama-1.1B-Chat-v1.0-Q3_K_M.gguf +2 -2
  6. TinyLlama-1.1B-Chat-v1.0-Q3_K_S.gguf +2 -2
  7. TinyLlama-1.1B-Chat-v1.0-Q4_0.gguf +2 -2
  8. TinyLlama-1.1B-Chat-v1.0-Q4_1.gguf +2 -2
  9. TinyLlama-1.1B-Chat-v1.0-Q4_K.gguf +2 -2
  10. TinyLlama-1.1B-Chat-v1.0-Q4_K_M.gguf +2 -2
  11. TinyLlama-1.1B-Chat-v1.0-Q4_K_S.gguf +2 -2
  12. TinyLlama-1.1B-Chat-v1.0-Q5_0.gguf +2 -2
  13. TinyLlama-1.1B-Chat-v1.0-Q5_1.gguf +2 -2
  14. TinyLlama-1.1B-Chat-v1.0-Q5_K.gguf +2 -2
  15. TinyLlama-1.1B-Chat-v1.0-Q5_K_M.gguf +2 -2
  16. TinyLlama-1.1B-Chat-v1.0-Q5_K_S.gguf +2 -2
  17. TinyLlama-1.1B-Chat-v1.0-Q6_K.gguf +2 -2
  18. TinyLlama-1.1B-Chat-v1.0-Q8_0.gguf +2 -2
  19. TinyLlama-1.1B-Chat-v1.0-f16.gguf +2 -2
  20. tokenizer.model +3 -0
README.md CHANGED
@@ -7,7 +7,21 @@ tags:
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  datasets:
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  - cerebras/SlimPajama-627B
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  - bigcode/starcoderdata
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- - OpenAssistant/oasst_top1_2023-08-25
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  quantized_by: andrijdavid
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  ---
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  # TinyLlama-1.1B-Chat-v1.0-GGUF
@@ -217,7 +231,7 @@ The TinyLlama project aims to **pretrain** a **1.1B Llama model on 3 trillion to
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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/edit/main/README.md)'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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  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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+ widget:
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+ - text: '<|system|>
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+
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+ You are a chatbot who can help code!</s>
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+
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+ <|user|>
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+
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+ Write me a function to calculate the first 10 digits of the fibonacci sequence
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+ in Python and print it out to the CLI.</s>
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+
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+ <|assistant|>
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+
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+ '
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  quantized_by: andrijdavid
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  ---
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  # TinyLlama-1.1B-Chat-v1.0-GGUF
 
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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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