[WIP] Upload folder using huggingface_hub (multi-commit c2a098e00dce61d54e471c607436031a7d151dd3f0e9f195ff80a2f4816a96d8)
#1
by
MaziyarPanahi
- opened
- README.md +0 -81
- added_tokens.json +0 -5
- config.json +0 -27
- generation_config.json +0 -7
- merges.txt +0 -0
- model-00001-of-00004.safetensors +0 -3
- model-00002-of-00004.safetensors +0 -3
- model-00003-of-00004.safetensors +0 -3
- model-00004-of-00004.safetensors +0 -3
- model.safetensors.index.json +0 -346
- qwen2-fine-tunes-maziyar-panahi.webp +0 -0
- special_tokens_map.json +0 -20
- tokenizer.json +0 -0
- tokenizer_config.json +0 -43
- vocab.json +0 -0
README.md
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---
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license: apache-2.0
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language:
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- en
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pipeline_tag: text-generation
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tags:
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- chat
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- qwen
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- qwen2
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- finetune
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- chatml
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- OpenHermes-2.5
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- HelpSteer2
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- Orca
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- SlimOrca
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library_name: transformers
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inference: false
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model_creator: MaziyarPanahi
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quantized_by: MaziyarPanahi
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base_model: Qwen/Qwen2-7B
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model_name: calme-2.5-qwen2-7b
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datasets:
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- nvidia/HelpSteer2
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- teknium/OpenHermes-2.5
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- microsoft/orca-math-word-problems-200k
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- Open-Orca/SlimOrca
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---
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<img src="./qwen2-fine-tunes-maziyar-panahi.webp" alt="Qwen2 fine-tune" width="500" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
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# MaziyarPanahi/calme-2.5-qwen2-7b
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This is a fine-tuned version of the `Qwen/Qwen2-7B` model. It aims to improve the base model across all benchmarks.
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# ⚡ Quantized GGUF
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All GGUF models are available here: [MaziyarPanahi/calme-2.5-qwen2-7b-GGUF](https://huggingface.co/MaziyarPanahi/calme-2.5-qwen2-7b-GGUF)
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# 🏆 [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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coming soon!
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# Prompt Template
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This model uses `ChatML` prompt template:
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```
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<|im_start|>system
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{System}
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<|im_end|>
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<|im_start|>user
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{User}
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<|im_end|>
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<|im_start|>assistant
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{Assistant}
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````
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# How to use
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```python
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# Use a pipeline as a high-level helper
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from transformers import pipeline
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messages = [
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{"role": "user", "content": "Who are you?"},
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]
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pipe = pipeline("text-generation", model="MaziyarPanahi/calme-2.5-qwen2-7b")
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pipe(messages)
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# Load model directly
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from transformers import AutoTokenizer, AutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("MaziyarPanahi/calme-2.5-qwen2-7b")
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model = AutoModelForCausalLM.from_pretrained("MaziyarPanahi/calme-2.5-qwen2-7b")
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```
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added_tokens.json
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}
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config.json
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{
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"_name_or_path": "Qwen/Qwen2-7B",
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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": 3584,
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"initializer_range": 0.02,
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"intermediate_size": 18944,
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"max_position_embeddings": 131072,
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"max_window_layers": 28,
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"model_type": "qwen2",
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"num_attention_heads": 28,
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"num_hidden_layers": 28,
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"num_key_value_heads": 4,
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"rms_norm_eps": 1e-06,
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"rope_theta": 1000000.0,
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"sliding_window": 131072,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.41.1",
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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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merges.txt
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qwen2-fine-tunes-maziyar-panahi.webp
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special_tokens_map.json
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tokenizer.json
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tokenizer_config.json
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