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bartowski
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blossom-v5-14b-exl2

Text Generation
Chinese
English
Model card Files Community
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Quant for 5.0

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Files changed (13) hide show
  1. README.md +20 -47
  2. added_tokens.json +5 -0
  3. config.json +28 -0
  4. generation_config.json +6 -0
  5. merges.txt +0 -0
  6. model.safetensors.index.json +490 -0
  7. original_repo_url.txt +1 -0
  8. output-00001-of-00002.safetensors +3 -0
  9. output-00002-of-00002.safetensors +3 -0
  10. special_tokens_map.json +20 -0
  11. tokenizer.json +0 -0
  12. tokenizer_config.json +43 -0
  13. vocab.json +0 -0
README.md CHANGED
@@ -8,68 +8,41 @@ datasets:
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  language:
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  - zh
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  - en
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- quantized_by: bartowski
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- pipeline_tag: text-generation
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  ---
 
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- ## Exllama v2 Quantizations of blossom-v5-14b
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- Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.15">turboderp's ExLlamaV2 v0.0.15</a> for quantization.
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- <b>The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)</b>
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- Each branch contains an individual bits per weight, with the main one containing only the meaurement.json for further conversions.
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- Original model: https://huggingface.co/Azure99/blossom-v5-14b
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- No GQA - VRAM requirements will be higher
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- | Branch | Bits | lm_head bits | VRAM (4k) | VRAM (16k) | Description |
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- | ----- | ---- | ------- | ------ | ------ | ------------ |
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- | [8_0](https://huggingface.co/bartowski/blossom-v5-14b-exl2/tree/8_0) | 8.0 | 8.0 | 18.5 GB | 28.8 GB | Near unquantized performance at vastly reduced size, **recommended**. |
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- | [6_5](https://huggingface.co/bartowski/blossom-v5-14b-exl2/tree/6_5) | 6.5 | 8.0 | 15.9 GB | 26.4 GB | Near unquantized performance at vastly reduced size, **recommended**. |
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- | [5_0](https://huggingface.co/bartowski/blossom-v5-14b-exl2/tree/5_0) | 5.0 | 6.0 | 13.3 GB | 23.9 GB | Slightly lower perplexity vs 6.5. |
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- | [4_25](https://huggingface.co/bartowski/blossom-v5-14b-exl2/tree/4_25) | 4.25 | 6.0 | 12.0 GB | 22.6 GB | GPTQ equivalent bits per weight, can fit in 12 GB card with lower context. |
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- | [3_75](https://huggingface.co/bartowski/blossom-v5-14b-exl2/tree/3_75) | 3.75 | 6.0 | 11.1 GB | 21.7 GB | Lower quality but still generally usable. |
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- | [3_0](https://huggingface.co/bartowski/blossom-v5-14b-exl2/tree/3_0) | 3.0 | 6.0 | 10.0 GB | 20.6 GB | Very low quality, not recommended unless you have to. |
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- VRAM requirements listed for both 4k context and 16k context since without GQA the differences are massive (9.6 GB)
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- ## Download instructions
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- With git:
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-
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- ```shell
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- git clone --single-branch --branch 6_5 https://huggingface.co/bartowski/blossom-v5-14b-exl2 blossom-v5-14b-exl2-6_5
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  ```
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-
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- With huggingface hub (credit to TheBloke for instructions):
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-
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- ```shell
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- pip3 install huggingface-hub
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  ```
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- To download the `main` (only useful if you only care about measurement.json) branch to a folder called `blossom-v5-14b-exl2`:
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- ```shell
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- mkdir blossom-v5-14b-exl2
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- huggingface-cli download bartowski/blossom-v5-14b-exl2 --local-dir blossom-v5-14b-exl2 --local-dir-use-symlinks False
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  ```
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-
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- To download from a different branch, add the `--revision` parameter:
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-
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- Linux:
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-
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- ```shell
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- mkdir blossom-v5-14b-exl2-6_5
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- huggingface-cli download bartowski/blossom-v5-14b-exl2 --revision 6_5 --local-dir blossom-v5-14b-exl2-6_5 --local-dir-use-symlinks False
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- ```
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-
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- Windows (which apparently doesn't like _ in folders sometimes?):
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-
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- ```shell
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- mkdir blossom-v5-14b-exl2-6.5
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- huggingface-cli download bartowski/blossom-v5-14b-exl2 --revision 6_5 --local-dir blossom-v5-14b-exl2-6.5 --local-dir-use-symlinks False
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  ```
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- Want to support my work? Visit my ko-fi page here: https://ko-fi.com/bartowski
 
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  language:
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  - zh
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  - en
 
 
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  ---
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+ # **BLOSSOM-v5-14b**
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+ [💻Github](https://github.com/Azure99/BlossomLM) • [🚀Blossom Chat Demo](https://blossom-chat.com/)
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+ ### What's new?
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+ The Blossom V5 series models is fully trained using high-quality data distilled from gpt-4-0125-preview, resulting in significant improvements.
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+ ### Introduction
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+ Blossom is a conversational large language model, fine-tuned on the Blossom Orca/Wizard/Chat/Math mixed dataset based on the Qwen1.5-14B pre-trained model. Blossom possesses robust general capabilities and context comprehension. Additionally, the high-quality Chinese and English datasets used for training have been made open source.
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+ Training was conducted in two stages. The first stage used 40K Wizard, 40K Orca, 10K Math single-turn instruction datasets, training for 1 epoch; the second stage used 10K Blossom chat multi-turn dialogue dataset, and 10% randomly sampled data from the first stage, training for 3 epochs.
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+ ### Inference
 
 
 
 
 
 
 
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+ Inference is performed in the form of dialogue continuation.
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+ Single-turn dialogue
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  ```
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+ A chat between a human and an artificial intelligence bot. The bot gives helpful, detailed, and polite answers to the human's questions.
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+ |Human|: hello
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+ |Bot|:
 
 
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  ```
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+ Multi-turn dialogue
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  ```
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+ A chat between a human and an artificial intelligence bot. The bot gives helpful, detailed, and polite answers to the human's questions.
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+ |Human|: hello
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+ |Bot|: Hello! How can I assist you today?<|endoftext|>
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+ |Human|: Generate a random number using python
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+ |Bot|:
 
 
 
 
 
 
 
 
 
 
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  ```
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+ Note: At the end of the Bot's output in the historical conversation, append a `<|endoftext|>`.
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config.json ADDED
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+ {
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+ "_name_or_path": "/mnt/output/qwen1_5-14b_5-stage1",
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+ "use_sliding_window": false,
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+ "vocab_size": 152064
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+ }
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