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Model: HumanLLMs/Human-Like-Mistral-Nemo-Instruct-2407 Source: Original Platform
2026-07-05 05:48:13 +08:00
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+---
+license: apache-2.0
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- axolotl
+- dpo
+- trl
+base_model: mistralai/Mistral-Nemo-Instruct-2407
+model-index:
+- name: Humanish-Mistral-Nemo-Instruct-2407
+  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: 54.51
+      name: strict accuracy
+    source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-Mistral-Nemo-Instruct-2407
+      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: 32.71
+      name: normalized accuracy
+    source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-Mistral-Nemo-Instruct-2407
+      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: 7.63
+      name: exact match
+    source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-Mistral-Nemo-Instruct-2407
+      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: 5.03
+      name: acc_norm
+    source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-Mistral-Nemo-Instruct-2407
+      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: 9.4
+      name: acc_norm
+    source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-Mistral-Nemo-Instruct-2407
+      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: 28.01
+      name: accuracy
+    source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-Mistral-Nemo-Instruct-2407
+      name: Open LLM Leaderboard
+datasets:
+- HumanLLMs/Human-Like-DPO-Dataset
+language:
+- en
+---
+<div align="center">
+  <img src="https://cdn-avatars.huggingface.co/v1/production/uploads/63da3d7ae697e5898cb86854/H-vpXOX6KZu01HnV87Jk5.jpeg" width="320" height="320" />
+  <h1>Enhancing Human-Like Responses in Large Language Models</h1>
+</div>
+
+<p align="center">
+  &nbsp&nbsp | 🤗 <a href="https://huggingface.co/collections/HumanLLMs/human-like-humanish-llms-6759fa68f22e11eb1a10967e">Models</a>&nbsp&nbsp | 
+  &nbsp&nbsp 📊 <a href="https://huggingface.co/datasets/HumanLLMs/Human-Like-DPO-Dataset">Dataset</a>&nbsp&nbsp | 
+  &nbsp&nbsp 📄<a href="https://arxiv.org/abs/2501.05032">Paper</a>&nbsp&nbsp |
+</p>
+
+<p align="center">
+  <b>📢 The paper associated with this model has been accepted to the <a href="https://personalizedllm.github.io/events/perfm-aaai26/">AAAI-26 Workshop on Personalization in the Era of Large Foundation Models (PerFM)</a>.</b>
+</p>
+
+# 🚀 Human-Like-Llama3-8B-Instruct
+
+This model is a fine-tuned version of [mistralai/Mistral-Nemo-Instruct-2407](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407), 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:** Mistral-Nemo-Instruct-2407 
+- **Framework:** Axolotl v0.4.1  
+- **Hardware:** 2x NVIDIA A100 (80 GB) GPUs  
+- **Training Time:** ~3 hours 40 minutes  
+- **Dataset:** Synthetic dataset with ≈11,000 samples across 256 diverse topics  
+
+<details><summary>See axolotl config</summary>
+
+axolotl version: `0.4.1`
+```yaml
+base_model: mistralai/Mistral-Nemo-Instruct-2407
+model_type: MistralForCausalLM
+tokenizer_type: AutoTokenizer
+
+load_in_8bit: true
+load_in_4bit: false
+strict: false
+
+chat_template: inst
+rl: dpo
+datasets:
+  - path: HumanLLMs/humanish-dpo-project
+    type: chatml.prompt_pairs
+    conversation: mistral
+
+dataset_prepared_path: last_run_prepared
+val_set_size: 0.05
+output_dir: ./humanish-mistral-nemo-instruct-2407
+
+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-Mistral-Nemo-Instruct-2407
+
+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:
+
+special_tokens:
+   pad_token: </s>
+
+save_safetensors: true
+```
+
+</details><br>
+
+# 💬 Prompt Template
+
+You can use Mistral-Nemo prompt template while using the model:
+
+### Mistral-Nemo
+
+```
+<s>[INST] Hello, how are you? [/INST]I'm doing great. How can I help you today?</s> [INST] I'd like to show off how chat templating works! [/INST]
+```
+
+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}, 
+}
+```
--- a/config.json
+++ b/config.json
@@ -0,0 +1,27 @@
+{
+  "_name_or_path": "mistralai/Mistral-Nemo-Instruct-2407",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 5120,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 1024000,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 40,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 1000000.0,
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.45.1",
+  "use_cache": false,
+  "vocab_size": 131072
+}
--- a/configuration.json
+++ b/configuration.json
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+{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
--- a/generation_config.json
+++ b/generation_config.json
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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "do_sample": true,
+  "eos_token_id": 2,
+  "transformers_version": "4.45.1"
+}
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