commit c5d102c03590651af3ddc6e7284bf9ec336f1696 Author: ModelHub XC Date: Wed May 6 07:00:38 2026 +0800 初始化项目，由ModelHub XC社区提供模型 Model: HumanLLMs/Human-Like-LLama3-8B-Instruct Source: Original Platform diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..26dfb80 --- /dev/null +++ b/.gitattributes @@ -0,0 +1,40 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text +tokenizer.json filter=lfs diff=lfs merge=lfs -text +model-00001-of-00004.safetensors filter=lfs diff=lfs merge=lfs -text +model-00002-of-00004.safetensors filter=lfs diff=lfs merge=lfs -text +model-00003-of-00004.safetensors filter=lfs diff=lfs merge=lfs -text +model-00004-of-00004.safetensors filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000..64f6b7b --- /dev/null +++ b/README.md @@ -0,0 +1,315 @@ +--- +license: llama3 +tags: +- axolotl +- dpo +- trl +base_model: meta-llama/Meta-Llama-3-8B-Instruct +datasets: +- HumanLLMs/Human-Like-DPO-Dataset +model-index: +- name: Humanish-LLama3.1-8B-Instruct + results: + - task: + type: text-generation + name: Text Generation + dataset: + name: IFEval (0-Shot) + type: HuggingFaceH4/ifeval + args: + num_few_shot: 0 + metrics: + - type: inst_level_strict_acc and prompt_level_strict_acc + value: 64.98 + name: strict accuracy + source: + url: >- + https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-LLama3.1-8B-Instruct + name: Open LLM Leaderboard + - task: + type: text-generation + name: Text Generation + dataset: + name: BBH (3-Shot) + type: BBH + args: + num_few_shot: 3 + metrics: + - type: acc_norm + value: 28.01 + name: normalized accuracy + source: + url: >- + https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-LLama3.1-8B-Instruct + name: Open LLM Leaderboard + - task: + type: text-generation + name: Text Generation + dataset: + name: MATH Lvl 5 (4-Shot) + type: hendrycks/competition_math + args: + num_few_shot: 4 + metrics: + - type: exact_match + value: 8.46 + name: exact match + source: + url: >- + https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-LLama3.1-8B-Instruct + name: Open LLM Leaderboard + - task: + type: text-generation + name: Text Generation + dataset: + name: GPQA (0-shot) + type: Idavidrein/gpqa + args: + num_few_shot: 0 + metrics: + - type: acc_norm + value: 0.78 + name: acc_norm + source: + url: >- + https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-LLama3.1-8B-Instruct + name: Open LLM Leaderboard + - task: + type: text-generation + name: Text Generation + dataset: + name: MuSR (0-shot) + type: TAUR-Lab/MuSR + args: + num_few_shot: 0 + metrics: + - type: acc_norm + value: 2 + name: acc_norm + source: + url: >- + https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-LLama3.1-8B-Instruct + name: Open LLM Leaderboard + - task: + type: text-generation + name: Text Generation + dataset: + name: MMLU-PRO (5-shot) + type: TIGER-Lab/MMLU-Pro + config: main + split: test + args: + num_few_shot: 5 + metrics: + - type: acc + value: 30.02 + name: accuracy + source: + url: >- + https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-LLama3.1-8B-Instruct + name: Open LLM Leaderboard +pipeline_tag: text-generation +library_name: transformers +--- +
+ +

Enhancing Human-Like Responses in Large Language Models

+
+ +

+    | 🤗 Models   | +    📊 Dataset   | +    📄Paper   | +

+ +

+ 📢 The paper associated with this model has been accepted to the AAAI-26 Workshop on Personalization in the Era of Large Foundation Models (PerFM). +

+ +# 🚀 Human-Like-Llama3-8B-Instruct + +This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct), specifically optimized to generate more human-like and conversational responses. + +The fine-tuning process employed both [Low-Rank Adaptation (LoRA)](https://arxiv.org/abs/2106.09685) and [Direct Preference Optimization (DPO)](https://arxiv.org/abs/2305.18290) to enhance natural language understanding, conversational coherence, and emotional intelligence in interactions. + +The proccess of creating this models is detailed in the research paper [“Enhancing Human-Like Responses in Large Language Models”](https://arxiv.org/abs/2501.05032). + +# 🛠️ Training Configuration + +- **Base Model:** Llama3-8B-Instruct +- **Framework:** Axolotl v0.4.1 +- **Hardware:** 2x NVIDIA A100 (80 GB) GPUs +- **Training Time:** ~2 hours 20 minutes +- **Dataset:** Synthetic dataset with ≈11,000 samples across 256 diverse topics + +
See axolotl config + +axolotl version: `0.4.1` +```yaml +base_model: meta-llama/Meta-Llama-3-8B-Instruct +model_type: LlamaForCausalLM +tokenizer_type: AutoTokenizer + +load_in_8bit: true +load_in_4bit: false +strict: false + +chat_template: llama3 +rl: dpo +datasets: + - path: HumanLLMs/humanish-dpo-project + type: llama3.prompt_pairs + chat_template: llama3 + +dataset_prepared_path: +val_set_size: 0.05 +output_dir: ./humanish-llama3-8b-instruct + +sequence_len: 8192 +sample_packing: false +pad_to_sequence_len: true + +adapter: lora +lora_model_dir: +lora_r: 8 +lora_alpha: 4 +lora_dropout: 0.05 +lora_target_linear: true +lora_fan_in_fan_out: + +wandb_project: Humanish-DPO +wandb_entity: +wandb_watch: +wandb_name: +wandb_log_model: + +hub_model_id: HumanLLMs/Humanish-LLama3.1-8B-Instruct + +gradient_accumulation_steps: 8 +micro_batch_size: 2 +num_epochs: 1 +optimizer: adamw_bnb_8bit +lr_scheduler: cosine +learning_rate: 0.0002 + +train_on_inputs: false +group_by_length: false +bf16: auto +fp16: +tf32: false + +gradient_checkpointing: true +early_stopping_patience: +resume_from_checkpoint: +local_rank: +logging_steps: 1 +xformers_attention: +flash_attention: true +s2_attention: + +warmup_steps: 10 +evals_per_epoch: 2 +eval_table_size: +eval_max_new_tokens: 128 +saves_per_epoch: 1 +debug: +deepspeed: +weight_decay: 0.0 +fsdp: +fsdp_config: + +save_safetensors: true + +``` + +

+ +# 💬 Prompt Template + +You can use Llama3 prompt template while using the model: + +### Llama3 + +``` +<|start_header_id|>system<|end_header_id|> +{system}<|eot_id|> + +<|start_header_id|>user<|end_header_id|> +{user}<|eot_id|> + +<|start_header_id|>assistant<|end_header_id|> +{assistant}<|eot_id|> +``` + +This prompt template is available as a [chat template](https://huggingface.co/docs/transformers/main/chat_templating), which means you can format messages using the +`tokenizer.apply_chat_template()` method: + +```python +messages = [ + {"role": "system", "content": "You are helpful AI asistant."}, + {"role": "user", "content": "Hello!"} +] +gen_input = tokenizer.apply_chat_template(message, return_tensors="pt") +model.generate(**gen_input) +``` + +# 🤖 Models + +| Model | Download | +|:---------------------:|:-----------------------------------------------------------------------:| +| Human-Like-Llama-3-8B-Instruct | 🤗 [HuggingFace](https://huggingface.co/HumanLLMs/Human-Like-LLama3-8B-Instruct) | +| Human-Like-Qwen-2.5-7B-Instruct | 🤗 [HuggingFace](https://huggingface.co/HumanLLMs/Human-Like-Qwen2.5-7B-Instruct) | +| Human-Like-Mistral-Nemo-Instruct | 🤗 [HuggingFace](https://huggingface.co/HumanLLMs/Human-Like-Mistral-Nemo-Instruct-2407) | + +# 🔄 Quantizationed versions + +## GGUF [@bartowski](https://huggingface.co/bartowski) + +- https://huggingface.co/bartowski/Human-Like-LLama3-8B-Instruct-GGUF + +- https://huggingface.co/bartowski/Human-Like-Qwen2.5-7B-Instruct-GGUF + +- https://huggingface.co/bartowski/Human-Like-Mistral-Nemo-Instruct-2407-GGUF + + +# 🎯 Benchmark Results + +| **Group** | **Model** | **Average** | **IFEval** | **BBH** | **MATH Lvl 5** | **GPQA** | **MuSR** | **MMLU-PRO** | +|--------------------------------|--------------------------------|-------------|------------|---------|----------------|----------|----------|--------------| +| **Llama Models** | Human-Like-Llama-3-8B-Instruct | 22.37 | **64.97** | 28.01 | 8.45 | 0.78 | **2.00** | 30.01 | +| | Llama-3-8B-Instruct | 23.57 | 74.08 | 28.24 | 8.68 | 1.23 | 1.60 | 29.60 | +| | *Difference (Human-Like)* | -1.20 | **-9.11** | -0.23 | -0.23 | -0.45 | +0.40 | +0.41 | +| **Qwen Models** | Human-Like-Qwen-2.5-7B-Instruct | 26.66 | 72.84 | 34.48 | 0.00 | 6.49 | 8.42 | 37.76 | +| | Qwen-2.5-7B-Instruct | 26.86 | 75.85 | 34.89 | 0.00 | 5.48 | 8.45 | 36.52 | +| | *Difference (Human-Like)* | -0.20 | -3.01 | -0.41 | 0.00 | **+1.01**| -0.03 | **+1.24** | +| **Mistral Models** | Human-Like-Mistral-Nemo-Instruct | 22.88 | **54.51** | 32.70 | 7.62 | 5.03 | 9.39 | 28.00 | +| | Mistral-Nemo-Instruct | 23.53 | 63.80 | 29.68 | 5.89 | 5.37 | 8.48 | 27.97 | +| | *Difference (Human-Like)* | -0.65 | **-9.29** | **+3.02**| **+1.73** | -0.34 | +0.91 | +0.03 | + + +# 📊 Dataset + +The dataset used for fine-tuning was generated using LLaMA 3 models. The dataset includes 10,884 samples across 256 distinct topics such as technology, daily life, science, history, and arts. Each sample consists of: + +- **Human-like responses:** Natural, conversational answers mimicking human dialogue. +- **Formal responses:** Structured and precise answers with a more formal tone. + +The dataset has been open-sourced and is available at: + +- 👉 [Human-Like-DPO-Dataset](https://huggingface.co/datasets/HumanLLMs/Human-Like-DPO-Dataset) + +More details on the dataset creation process can be found in the accompanying research paper. + +# 📝 Citation + +``` +@misc{çalık2025enhancinghumanlikeresponseslarge, + title={Enhancing Human-Like Responses in Large Language Models}, + author={Ethem Yağız Çalık and Talha Rüzgar Akkuş}, + year={2025}, + eprint={2501.05032}, + archivePrefix={arXiv}, + primaryClass={cs.CL}, + url={https://arxiv.org/abs/2501.05032}, +} +``` \ No newline at end of file diff --git a/config.json b/config.json new file mode 100644 index 0000000..6fed4e6 --- /dev/null +++ b/config.json @@ -0,0 +1,30 @@ +{ + "_name_or_path": "meta-llama/Meta-Llama-3-8B-Instruct", + 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"normalized": false, + "rstrip": false, + "single_word": false, + "special": true + } + }, + "bos_token": "<|begin_of_text|>", + "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>\n\n' }}{% endif %}", + "clean_up_tokenization_spaces": true, + "eos_token": "<|eot_id|>", + "model_input_names": [ + "input_ids", + "attention_mask" + ], + "model_max_length": 1000000000000000019884624838656, + "pad_token": "<|begin_of_text|>", + "tokenizer_class": "PreTrainedTokenizerFast" +}