LoneStriker
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Browse files- README.md +63 -0
- added_tokens.json +5 -0
- config.json +27 -0
- generation_config.json +9 -0
- merges.txt +0 -0
- model.safetensors.index.json +490 -0
- output-00001-of-00002.safetensors +3 -0
- output-00002-of-00002.safetensors +3 -0
- quyen.webp +0 -0
- special_tokens_map.json +20 -0
- tokenizer.json +0 -0
- tokenizer_config.json +43 -0
- vocab.json +0 -0
README.md
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---
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library_name: transformers
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license: other
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datasets:
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- teknium/OpenHermes-2.5
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- LDJnr/Capybara
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- Intel/orca_dpo_pairs
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- argilla/distilabel-capybara-dpo-7k-binarized
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language:
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- en
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pipeline_tag: text-generation
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---
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# Quyen
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<img src="quyen.webp" width="512" height="512" alt="Quyen">
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# Model Description
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Quyen is our first flagship LLM series based on the Qwen1.5 family. We introduced 6 different versions:
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- **Quyen-SE (0.5B)**
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- **Quyen-Mini (1.8B)**
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- **Quyen (4B)**
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- **Quyen-Plus (7B)**
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- **Quyen-Pro (14B)**
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- **Quyen-Pro-Max (72B)**
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All models were trained with SFT and DPO using the following dataset:
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- *OpenHermes-2.5* by **Teknium**
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- *Capyabara* by **LDJ**
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- *argilla/distilabel-capybara-dpo-7k-binarized* by **argilla**
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- *orca_dpo_pairs* by **Intel**
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- and Private Data by **Ontocord** & **BEE-spoke-data**
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# Prompt Template
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- All Quyen models use ChatML as the default template:
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```
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<|im_start|>system
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You are a sentient, superintelligent artificial general intelligence, here to teach and assist me.<|im_end|>
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<|im_start|>user
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Hello world.<|im_end|>
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<|im_start|>assistant
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```
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- You can also use `apply_chat_template`:
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```python
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messages = [
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{"role": "system", "content": "You are a sentient, superintelligent artificial general intelligence, here to teach and assist me."},
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{"role": "user", "content": "Hello world."}
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]
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gen_input = tokenizer.apply_chat_template(message, return_tensors="pt")
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model.generate(**gen_input)
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```
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# Benchmarks:
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- Coming Soon! We will update the benchmarks later
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# Acknowledgement
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- We're incredibly grateful to **Tensoic** and **Ontocord** for their generous support with compute and data preparation.
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- Special thanks to the Qwen team for letting us access the models early for these amazing finetunes.
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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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{
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"_name_or_path": "Qwen/Qwen2-beta-14B",
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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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"eos_token_id": 151645,
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"hidden_act": "silu",
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"hidden_size": 5120,
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"initializer_range": 0.02,
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"intermediate_size": 13696,
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"max_position_embeddings": 32768,
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"max_window_layers": 35,
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"model_type": "qwen2",
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"num_attention_heads": 40,
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"num_hidden_layers": 40,
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"num_key_value_heads": 40,
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"rms_norm_eps": 1e-06,
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"rope_theta": 1000000.0,
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"sliding_window": 4096,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.38.0.dev0",
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"use_cache": false,
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"use_sliding_window": false,
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"vocab_size": 152064
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}
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generation_config.json
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{
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"bos_token_id": 151643,
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"do_sample": true,
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"eos_token_id": [
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151645,
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151643
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],
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"transformers_version": "4.38.0.dev0"
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}
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merges.txt
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The diff for this file is too large to render.
See raw diff
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model.safetensors.index.json
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{
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},
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