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Model: Azure99/blossom-v5-4b Source: Original Platform
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README.md
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README.md
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---
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license: apache-2.0
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datasets:
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- Azure99/blossom-chat-v3
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- Azure99/blossom-math-v4
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- Azure99/blossom-wizard-v3
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- Azure99/blossom-orca-v3
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language:
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- zh
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- en
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---
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# **BLOSSOM-v5-4b**
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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 Qwen1.5-4B 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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added_tokens.json
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added_tokens.json
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{
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"<|endoftext|>": 151643,
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"<|im_end|>": 151645,
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"<|im_start|>": 151644
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}
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config.json
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config.json
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{
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"_name_or_path": "/mnt/output/qwen1_5-4b_5-stage1",
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"architectures": [
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"Qwen2ForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 151643,
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"eos_token_id": 151643,
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"hidden_act": "silu",
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"hidden_size": 2560,
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"initializer_range": 0.02,
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"intermediate_size": 6912,
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"max_position_embeddings": 32768,
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"max_window_layers": 21,
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"model_type": "qwen2",
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"num_attention_heads": 20,
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"num_hidden_layers": 40,
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"num_key_value_heads": 20,
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"rms_norm_eps": 1e-06,
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"rope_theta": 5000000.0,
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"sliding_window": 32768,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.38.2",
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"use_cache": true,
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"use_sliding_window": false,
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"vocab_size": 151936
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}
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generation_config.json
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generation_config.json
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{
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"bos_token_id": 151643,
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"eos_token_id": 151643,
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"transformers_version": "4.38.2",
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"do_sample": true,
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"temperature": 0.5,
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"top_p": 0.85,
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"repetition_penalty": 1.05
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}
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merges.txt
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merges.txt
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model.safetensors
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 7900794008
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special_tokens_map.json
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special_tokens_map.json
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{
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"additional_special_tokens": [
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"<|im_start|>",
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"<|im_end|>"
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],
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"eos_token": {
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": {
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"content": "<|endoftext|>",
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"normalized": false,
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"rstrip": false,
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"single_word": false
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}
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}
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tokenizer.json
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tokenizer.json
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tokenizer_config.json
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{
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"add_prefix_space": false,
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"151643": {
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"content": "<|endoftext|>",
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"normalized": false,
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"rstrip": false,
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"additional_special_tokens": [
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"<|im_start|>",
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"<|im_end|>"
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],
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"bos_token": null,
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"chat_template": "A chat between a human and an artificial intelligence bot. The bot gives helpful, detailed, and polite answers to the human's questions.\n{% for message in messages %}{% set content = message['content'] %}{% if message['role'] == 'user' %}{{ '|Human|: ' + content + '\\n|Bot|: ' }}{% elif message['role'] == 'assistant' %}{{ content + '<|endoftext|>\\n' }}{% endif %}{% endfor %}",
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"clean_up_tokenization_spaces": false,
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"eos_token": "<|endoftext|>",
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"errors": "replace",
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"model_max_length": 32768,
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"pad_token": "<|endoftext|>",
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"padding_side": "left",
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"split_special_tokens": false,
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"tokenizer_class": "Qwen2Tokenizer",
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"unk_token": null
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}
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vocab.json
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vocab.json
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