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README.md

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+Quantization made by Richard Erkhov.
+
+[Github](https://github.com/RichardErkhov)
+
+[Discord](https://discord.gg/pvy7H8DZMG)
+
+[Request more models](https://github.com/RichardErkhov/quant_request)
+
+
+NeuralHermes-2.5-Mistral-7B-laser - GGUF
+- Model creator: https://huggingface.co/mlabonne/
+- Original model: https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B-laser/
+
+
+| Name | Quant method | Size |
+| ---- | ---- | ---- |
+| [NeuralHermes-2.5-Mistral-7B-laser.Q2_K.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_NeuralHermes-2.5-Mistral-7B-laser-gguf/blob/main/NeuralHermes-2.5-Mistral-7B-laser.Q2_K.gguf) | Q2_K | 2.53GB |
+| [NeuralHermes-2.5-Mistral-7B-laser.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_NeuralHermes-2.5-Mistral-7B-laser-gguf/blob/main/NeuralHermes-2.5-Mistral-7B-laser.IQ3_XS.gguf) | IQ3_XS | 2.81GB |
+| [NeuralHermes-2.5-Mistral-7B-laser.IQ3_S.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_NeuralHermes-2.5-Mistral-7B-laser-gguf/blob/main/NeuralHermes-2.5-Mistral-7B-laser.IQ3_S.gguf) | IQ3_S | 2.96GB |
+| [NeuralHermes-2.5-Mistral-7B-laser.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_NeuralHermes-2.5-Mistral-7B-laser-gguf/blob/main/NeuralHermes-2.5-Mistral-7B-laser.Q3_K_S.gguf) | Q3_K_S | 2.95GB |
+| [NeuralHermes-2.5-Mistral-7B-laser.IQ3_M.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_NeuralHermes-2.5-Mistral-7B-laser-gguf/blob/main/NeuralHermes-2.5-Mistral-7B-laser.IQ3_M.gguf) | IQ3_M | 3.06GB |
+| [NeuralHermes-2.5-Mistral-7B-laser.Q3_K.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_NeuralHermes-2.5-Mistral-7B-laser-gguf/blob/main/NeuralHermes-2.5-Mistral-7B-laser.Q3_K.gguf) | Q3_K | 3.28GB |
+| [NeuralHermes-2.5-Mistral-7B-laser.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_NeuralHermes-2.5-Mistral-7B-laser-gguf/blob/main/NeuralHermes-2.5-Mistral-7B-laser.Q3_K_M.gguf) | Q3_K_M | 3.28GB |
+| [NeuralHermes-2.5-Mistral-7B-laser.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_NeuralHermes-2.5-Mistral-7B-laser-gguf/blob/main/NeuralHermes-2.5-Mistral-7B-laser.Q3_K_L.gguf) | Q3_K_L | 3.56GB |
+| [NeuralHermes-2.5-Mistral-7B-laser.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_NeuralHermes-2.5-Mistral-7B-laser-gguf/blob/main/NeuralHermes-2.5-Mistral-7B-laser.IQ4_XS.gguf) | IQ4_XS | 3.67GB |
+| [NeuralHermes-2.5-Mistral-7B-laser.Q4_0.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_NeuralHermes-2.5-Mistral-7B-laser-gguf/blob/main/NeuralHermes-2.5-Mistral-7B-laser.Q4_0.gguf) | Q4_0 | 3.83GB |
+| [NeuralHermes-2.5-Mistral-7B-laser.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_NeuralHermes-2.5-Mistral-7B-laser-gguf/blob/main/NeuralHermes-2.5-Mistral-7B-laser.IQ4_NL.gguf) | IQ4_NL | 3.87GB |
+| [NeuralHermes-2.5-Mistral-7B-laser.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_NeuralHermes-2.5-Mistral-7B-laser-gguf/blob/main/NeuralHermes-2.5-Mistral-7B-laser.Q4_K_S.gguf) | Q4_K_S | 3.86GB |
+| [NeuralHermes-2.5-Mistral-7B-laser.Q4_K.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_NeuralHermes-2.5-Mistral-7B-laser-gguf/blob/main/NeuralHermes-2.5-Mistral-7B-laser.Q4_K.gguf) | Q4_K | 4.07GB |
+| [NeuralHermes-2.5-Mistral-7B-laser.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_NeuralHermes-2.5-Mistral-7B-laser-gguf/blob/main/NeuralHermes-2.5-Mistral-7B-laser.Q4_K_M.gguf) | Q4_K_M | 4.07GB |
+| [NeuralHermes-2.5-Mistral-7B-laser.Q4_1.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_NeuralHermes-2.5-Mistral-7B-laser-gguf/blob/main/NeuralHermes-2.5-Mistral-7B-laser.Q4_1.gguf) | Q4_1 | 4.24GB |
+| [NeuralHermes-2.5-Mistral-7B-laser.Q5_0.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_NeuralHermes-2.5-Mistral-7B-laser-gguf/blob/main/NeuralHermes-2.5-Mistral-7B-laser.Q5_0.gguf) | Q5_0 | 4.65GB |
+| [NeuralHermes-2.5-Mistral-7B-laser.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_NeuralHermes-2.5-Mistral-7B-laser-gguf/blob/main/NeuralHermes-2.5-Mistral-7B-laser.Q5_K_S.gguf) | Q5_K_S | 4.65GB |
+| [NeuralHermes-2.5-Mistral-7B-laser.Q5_K.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_NeuralHermes-2.5-Mistral-7B-laser-gguf/blob/main/NeuralHermes-2.5-Mistral-7B-laser.Q5_K.gguf) | Q5_K | 4.78GB |
+| [NeuralHermes-2.5-Mistral-7B-laser.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_NeuralHermes-2.5-Mistral-7B-laser-gguf/blob/main/NeuralHermes-2.5-Mistral-7B-laser.Q5_K_M.gguf) | Q5_K_M | 4.78GB |
+| [NeuralHermes-2.5-Mistral-7B-laser.Q5_1.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_NeuralHermes-2.5-Mistral-7B-laser-gguf/blob/main/NeuralHermes-2.5-Mistral-7B-laser.Q5_1.gguf) | Q5_1 | 5.07GB |
+| [NeuralHermes-2.5-Mistral-7B-laser.Q6_K.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_NeuralHermes-2.5-Mistral-7B-laser-gguf/blob/main/NeuralHermes-2.5-Mistral-7B-laser.Q6_K.gguf) | Q6_K | 5.53GB |
+| [NeuralHermes-2.5-Mistral-7B-laser.Q8_0.gguf](https://huggingface.co/RichardErkhov/mlabonne_-_NeuralHermes-2.5-Mistral-7B-laser-gguf/blob/main/NeuralHermes-2.5-Mistral-7B-laser.Q8_0.gguf) | Q8_0 | 7.17GB |
+
+
+
+
+Original model description:
+---
+language:
+- en
+license: apache-2.0
+tags:
+- mistral
+- instruct
+- finetune
+- chatml
+- gpt4
+- synthetic data
+- distillation
+- dpo
+- rlhf
+- laser
+datasets:
+- mlabonne/chatml_dpo_pairs
+base_model: teknium/OpenHermes-2.5-Mistral-7B
+model-index:
+- name: NeuralHermes-2.5-Mistral-7B-laser
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: AI2 Reasoning Challenge (25-Shot)
+      type: ai2_arc
+      config: ARC-Challenge
+      split: test
+      args:
+        num_few_shot: 25
+    metrics:
+    - type: acc_norm
+      value: 66.38
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/NeuralHermes-2.5-Mistral-7B-laser
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: HellaSwag (10-Shot)
+      type: hellaswag
+      split: validation
+      args:
+        num_few_shot: 10
+    metrics:
+    - type: acc_norm
+      value: 85.09
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/NeuralHermes-2.5-Mistral-7B-laser
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU (5-Shot)
+      type: cais/mmlu
+      config: all
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 63.43
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/NeuralHermes-2.5-Mistral-7B-laser
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: TruthfulQA (0-shot)
+      type: truthful_qa
+      config: multiple_choice
+      split: validation
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: mc2
+      value: 54.95
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/NeuralHermes-2.5-Mistral-7B-laser
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: Winogrande (5-shot)
+      type: winogrande
+      config: winogrande_xl
+      split: validation
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 78.14
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/NeuralHermes-2.5-Mistral-7B-laser
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GSM8k (5-shot)
+      type: gsm8k
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 55.72
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/NeuralHermes-2.5-Mistral-7B-laser
+      name: Open LLM Leaderboard
+---
+
+<center><img src="https://i.imgur.com/gUlEJuU.jpeg"></center>
+
+# NeuralHermes 2.5 - Mistral 7B - LASER
+
+This is an experimental LASER version of NeuralHermes using [laserRMT](https://github.com/cognitivecomputations/laserRMT), based on [this paper](https://arxiv.org/pdf/2312.13558.pdf).
+
+|                                                Model                                                 |AGIEval|GPT4All|TruthfulQA|Bigbench|Average|
+|------------------------------------------------------------------------------------------------------|------:|------:|---------:|-------:|------:|
+|[NeuralHermes-2.5-Mistral-7B-laser](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B-laser)|  43.54|  73.44|     55.26|   42.24|  53.62|
+|[NeuralHermes-2.5-Mistral-7B](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B)            |  43.67|  73.24|     55.37|   41.76|  53.51|
+
+Fernando Fernandes Neto and Eric Hartford. "Optimizing Large Language Models Using Layer-Selective Rank Reduction and Random Matrix Theory." 2024.
+
+NeuralHermes is an [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) model that has been further fine-tuned with Direct Preference Optimization (DPO) using the [mlabonne/chatml_dpo_pairs](https://huggingface.co/datasets/mlabonne/chatml_dpo_pairs) dataset. It surpasses the original model on several benchmarks (see results).
+
+It is directly inspired by the RLHF process described by [Intel/neural-chat-7b-v3-1](https://huggingface.co/Intel/neural-chat-7b-v3-1)'s authors to improve performance. I used the same dataset and reformatted it to apply the ChatML template.
+
+The code to train this model is available on [Google Colab](https://colab.research.google.com/drive/15iFBr1xWgztXvhrj5I9fBv20c7CFOPBE?usp=sharing) and [GitHub](https://github.com/mlabonne/llm-course/tree/main). It required an A100 GPU for about an hour.
+
+## Results
+
+### AGIEval
+|             Task             |Version| Metric |Value|   |Stderr|
+|------------------------------|------:|--------|----:|---|-----:|
+|agieval_aqua_rat              |      0|acc     |21.26|±  |  2.57|
+|                              |       |acc_norm|22.83|±  |  2.64|
+|agieval_logiqa_en             |      0|acc     |39.32|±  |  1.92|
+|                              |       |acc_norm|40.71|±  |  1.93|
+|agieval_lsat_ar               |      0|acc     |25.65|±  |  2.89|
+|                              |       |acc_norm|25.65|±  |  2.89|
+|agieval_lsat_lr               |      0|acc     |48.82|±  |  2.22|
+|                              |       |acc_norm|50.00|±  |  2.22|
+|agieval_lsat_rc               |      0|acc     |58.36|±  |  3.01|
+|                              |       |acc_norm|57.25|±  |  3.02|
+|agieval_sat_en                |      0|acc     |74.27|±  |  3.05|
+|                              |       |acc_norm|73.30|±  |  3.09|
+|agieval_sat_en_without_passage|      0|acc     |43.69|±  |  3.46|
+|                              |       |acc_norm|42.23|±  |  3.45|
+|agieval_sat_math              |      0|acc     |37.27|±  |  3.27|
+|                              |       |acc_norm|36.36|±  |  3.25|
+
+Average: 43.54%
+
+### GPT4All
+|    Task     |Version| Metric |Value|   |Stderr|
+|-------------|------:|--------|----:|---|-----:|
+|arc_challenge|      0|acc     |57.76|±  |  1.44|
+|             |       |acc_norm|60.32|±  |  1.43|
+|arc_easy     |      0|acc     |83.84|±  |  0.76|
+|             |       |acc_norm|81.10|±  |  0.80|
+|boolq        |      1|acc     |86.70|±  |  0.59|
+|hellaswag    |      0|acc     |63.15|±  |  0.48|
+|             |       |acc_norm|82.55|±  |  0.38|
+|openbookqa   |      0|acc     |34.40|±  |  2.13|
+|             |       |acc_norm|45.20|±  |  2.23|
+|piqa         |      0|acc     |81.94|±  |  0.90|
+|             |       |acc_norm|82.97|±  |  0.88|
+|winogrande   |      0|acc     |75.22|±  |  1.21|
+
+Average: 73.44%
+
+### TruthfulQA
+|    Task     |Version|Metric|Value|   |Stderr|
+|-------------|------:|------|----:|---|-----:|
+|truthfulqa_mc|      1|mc1   |37.70|±  |  1.70|
+|             |       |mc2   |55.26|±  |  1.52|
+
+Average: 55.26%
+
+### Bigbench
+|                      Task                      |Version|       Metric        |Value|   |Stderr|
+|------------------------------------------------|------:|---------------------|----:|---|-----:|
+|bigbench_causal_judgement                       |      0|multiple_choice_grade|53.16|±  |  3.63|
+|bigbench_date_understanding                     |      0|multiple_choice_grade|65.31|±  |  2.48|
+|bigbench_disambiguation_qa                      |      0|multiple_choice_grade|34.11|±  |  2.96|
+|bigbench_geometric_shapes                       |      0|multiple_choice_grade|27.02|±  |  2.35|
+|                                                |       |exact_str_match      | 0.28|±  |  0.28|
+|bigbench_logical_deduction_five_objects         |      0|multiple_choice_grade|27.80|±  |  2.01|
+|bigbench_logical_deduction_seven_objects        |      0|multiple_choice_grade|19.86|±  |  1.51|
+|bigbench_logical_deduction_three_objects        |      0|multiple_choice_grade|48.33|±  |  2.89|
+|bigbench_movie_recommendation                   |      0|multiple_choice_grade|41.40|±  |  2.20|
+|bigbench_navigate                               |      0|multiple_choice_grade|50.00|±  |  1.58|
+|bigbench_reasoning_about_colored_objects        |      0|multiple_choice_grade|65.00|±  |  1.07|
+|bigbench_ruin_names                             |      0|multiple_choice_grade|46.21|±  |  2.36|
+|bigbench_salient_translation_error_detection    |      0|multiple_choice_grade|27.25|±  |  1.41|
+|bigbench_snarks                                 |      0|multiple_choice_grade|70.72|±  |  3.39|
+|bigbench_sports_understanding                   |      0|multiple_choice_grade|65.72|±  |  1.51|
+|bigbench_temporal_sequences                     |      0|multiple_choice_grade|30.40|±  |  1.46|
+|bigbench_tracking_shuffled_objects_five_objects |      0|multiple_choice_grade|22.56|±  |  1.18|
+|bigbench_tracking_shuffled_objects_seven_objects|      0|multiple_choice_grade|17.09|±  |  0.90|
+|bigbench_tracking_shuffled_objects_three_objects|      0|multiple_choice_grade|48.33|±  |  2.89|
+
+Average: 42.24%
+
+Average score: 53.62%
+
+## Usage
+
+You can run this model using [LM Studio](https://lmstudio.ai/) or any other frontend.
+
+You can also run this model using the following code:
+
+```python
+import transformers
+from transformers import AutoTokenizer
+
+# Format prompt
+message = [
+    {"role": "system", "content": "You are a helpful assistant chatbot."},
+    {"role": "user", "content": "What is a Large Language Model?"}
+]
+tokenizer = AutoTokenizer.from_pretrained(new_model)
+prompt = tokenizer.apply_chat_template(message, add_generation_prompt=True, tokenize=False)
+
+# Create pipeline
+pipeline = transformers.pipeline(
+    "text-generation",
+    model="mlabonne/NeuralHermes-2.5-Mistral-7B-laser",
+    tokenizer=tokenizer
+)
+
+# Generate text
+sequences = pipeline(
+    prompt,
+    do_sample=True,
+    temperature=0.7,
+    top_p=0.9,
+    num_return_sequences=1,
+    max_length=200,
+)
+print(sequences[0]['generated_text'])
+```
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_mlabonne__NeuralHermes-2.5-Mistral-7B-laser)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |67.29|
+|AI2 Reasoning Challenge (25-Shot)|66.38|
+|HellaSwag (10-Shot)              |85.09|
+|MMLU (5-Shot)                    |63.43|
+|TruthfulQA (0-shot)              |54.95|
+|Winogrande (5-shot)              |78.14|
+|GSM8k (5-shot)                   |55.72|
+
+
+