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README.md

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+---
+language:
+  - en
+license: apache-2.0
+datasets:
+  - databricks/databricks-dolly-15k
+  - Felladrin/ChatML-databricks-dolly-15k
+  - euclaise/reddit-instruct-curated
+  - Felladrin/ChatML-reddit-instruct-curated
+  - THUDM/webglm-qa
+  - Felladrin/ChatML-WebGLM-QA
+  - starfishmedical/webGPT_x_dolly
+  - Felladrin/ChatML-webGPT_x_dolly
+  - LDJnr/Capybara
+  - Felladrin/ChatML-Capybara
+  - Open-Orca/SlimOrca-Dedup
+  - Felladrin/ChatML-SlimOrca-Dedup
+  - HuggingFaceH4/ultrachat_200k
+  - Felladrin/ChatML-ultrachat_200k
+  - nvidia/HelpSteer
+  - Felladrin/ChatML-HelpSteer
+  - sablo/oasst2_curated
+  - Felladrin/ChatML-oasst2_curated
+  - CohereForAI/aya_dataset
+  - Felladrin/ChatML-aya_dataset
+  - argilla/distilabel-capybara-dpo-7k-binarized
+  - Felladrin/ChatML-distilabel-capybara-dpo-7k-binarized
+  - argilla/distilabel-intel-orca-dpo-pairs
+  - Felladrin/ChatML-distilabel-intel-orca-dpo-pairs
+  - argilla/ultrafeedback-binarized-preferences
+  - Felladrin/ChatML-ultrafeedback-binarized-preferences
+  - sablo/oasst2_dpo_pairs_en
+  - Felladrin/ChatML-oasst2_dpo_pairs_en
+  - NeuralNovel/Neural-DPO
+  - Felladrin/ChatML-Neural-DPO
+base_model: Felladrin/Minueza-32M-Base
+pipeline_tag: text-generation
+widget:
+  - messages:
+      - role: system
+        content:
+          You are a career counselor. The user will provide you with an individual
+          looking for guidance in their professional life, and your task is to assist
+          them in determining what careers they are most suited for based on their skills,
+          interests, and experience. You should also conduct research into the various
+          options available, explain the job market trends in different industries, and
+          advice on which qualifications would be beneficial for pursuing particular fields.
+      - role: user
+        content: Heya!
+      - role: assistant
+        content: Hi! How may I help you?
+      - role: user
+        content:
+          I am interested in developing a career in software engineering. What
+          would you recommend me to do?
+  - messages:
+      - role: system
+        content:
+          You are a highly knowledgeable assistant. Help the user as much as you
+          can.
+      - role: user
+        content: How can I become a healthier person?
+  - messages:
+      - role: system
+        content: You are a helpful assistant who gives creative responses.
+      - role: user
+        content: Write the specs of a game about mages in a fantasy world.
+  - messages:
+      - role: system
+        content: You are a helpful assistant who answers user's questions with details.
+      - role: user
+        content: Tell me about the pros and cons of social media.
+  - messages:
+      - role: system
+        content:
+          You are a helpful assistant who answers user's questions with details
+          and curiosity.
+      - role: user
+        content: What are some potential applications for quantum computing?
+inference:
+  parameters:
+    max_new_tokens: 250
+    do_sample: true
+    temperature: 0.65
+    top_p: 0.55
+    top_k: 35
+    repetition_penalty: 1.176
+---
+
+# Minueza-32Mx2-Chat
+
+- Base model: [Felladrin/Minueza-32M-Base](https://huggingface.co/Felladrin/Minueza-32M-Base)
+- Datasets used during SFT:
+  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-databricks-dolly-15k)] [databricks/databricks-dolly-15k](https://huggingface.co/datasets/databricks/databricks-dolly-15k)
+  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-reddit-instruct-curated)] [euclaise/reddit-instruct-curated](https://huggingface.co/datasets/euclaise/reddit-instruct-curated)
+  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-WebGLM-QA)] [THUDM/webglm-qa](https://huggingface.co/datasets/THUDM/webglm-qa)
+  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-webGPT_x_dolly)] [starfishmedical/webGPT_x_dolly](https://huggingface.co/datasets/starfishmedical/webGPT_x_dolly)
+  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-Capybara)] [LDJnr/Capybara](https://huggingface.co/datasets/LDJnr/Capybara)
+  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-SlimOrca-Dedup)] [Open-Orca/SlimOrca-Dedup](https://huggingface.co/datasets/Open-Orca/SlimOrca-Dedup)
+  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-ultrachat_200k)] [HuggingFaceH4/ultrachat_200k](https://huggingface.co/datasets/HuggingFaceH4/ultrachat_200k)
+  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-HelpSteer)] [nvidia/HelpSteer](https://huggingface.co/datasets/nvidia/HelpSteer)
+  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-oasst2_curated)] [sablo/oasst2_curated](https://huggingface.co/datasets/sablo/oasst2_curated)
+  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-aya_dataset)] [CohereForAI/aya_dataset](https://huggingface.co/datasets/CohereForAI/aya_dataset)
+- Datasets used during DPO:
+  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-distilabel-capybara-dpo-7k-binarized)] [argilla/distilabel-capybara-dpo-7k-binarized](https://huggingface.co/datasets/argilla/distilabel-capybara-dpo-7k-binarized)
+  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-distilabel-intel-orca-dpo-pairs)] [argilla/distilabel-intel-orca-dpo-pairs](https://huggingface.co/datasets/argilla/distilabel-intel-orca-dpo-pairs)
+  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-ultrafeedback-binarized-preferences)] [argilla/ultrafeedback-binarized-preferences](https://huggingface.co/datasets/argilla/ultrafeedback-binarized-preferences)
+  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-oasst2_dpo_pairs_en)] [sablo/oasst2_dpo_pairs_en](https://huggingface.co/datasets/sablo/oasst2_dpo_pairs_en)
+  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-Neural-DPO)] [NeuralNovel/Neural-DPO](https://huggingface.co/datasets/NeuralNovel/Neural-DPO)
+- License: [Apache License 2.0](https://huggingface.co/Felladrin/Minueza-32Mx2-Chat/resolve/main/license.txt)
+
+## Recommended Prompt Format
+
+```
+<|im_start|>system
+{system_message}<|im_end|>
+<|im_start|>user
+{user_message}<|im_end|>
+<|im_start|>assistant
+```
+
+## Recommended Inference Parameters
+
+```yml
+do_sample: true
+temperature: 0.65
+top_p: 0.55
+top_k: 35
+repetition_penalty: 1.176
+```
+
+## Usage Example
+
+```python
+from transformers import pipeline
+
+generate = pipeline("text-generation", "Felladrin/Minueza-32Mx2-Chat")
+
+messages = [
+    {
+        "role": "system",
+        "content": "You are a helpful assistant who answers the user's questions with details and curiosity.",
+    },
+    {
+        "role": "user",
+        "content": "What are some potential applications for quantum computing?",
+    },
+]
+
+prompt = generate.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+
+output = generate(
+    prompt,
+    max_new_tokens=256,
+    do_sample=True,
+    temperature=0.65,
+    top_k=35,
+    top_p=0.55,
+    repetition_penalty=1.176,
+)
+
+print(output[0]["generated_text"])
+```
+
+## How it was trained
+
+This model was trained with [SFT Trainer](https://huggingface.co/docs/trl/main/en/sft_trainer) and [DPO Trainer](https://huggingface.co/docs/trl/main/en/dpo_trainer), in several sessions, using the following settings:
+
+For Supervised Fine-Tuning:
+
+| Hyperparameter         | Value                                         |
+| :--------------------- | :-------------------------------------------- |
+| Learning rate          | 2e-6                                          |
+| Total train batch size | 16                                            |
+| Max. sequence length   | 2048                                          |
+| Weight decay           | 0.01                                          |
+| Warmup ratio           | 0.1                                           |
+| Optimizer              | Adam with betas=(0.9,0.999) and epsilon=1e-08 |
+| Scheduler              | cosine                                        |
+| Seed                   | 42                                            |
+| Neftune Noise Alpha    | 5                                             |
+
+For Direct Preference Optimization:
+
+| Hyperparameter         | Value |
+| :--------------------- | :---- |
+| Learning rate          | 5e-7  |
+| Total train batch size | 16    |
+| Max. length            | 1024  |
+| Max. prompt length     | 512   |
+| Max. steps             | 200   |
+| Weight decay           | 0     |
+| Warmup ratio           | 0.1   |
+| Beta                   | 0.1   |

added_tokens.json

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+{
+  "<|im_end|>": 32000,
+  "<|im_start|>": 32001
+}

config.json

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+{
+  "architectures": ["MixtralForCausalLM"],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 32000,
+  "hidden_act": "silu",
+  "hidden_size": 312,
+  "initializer_range": 0.02,
+  "intermediate_size": 1092,
+  "max_position_embeddings": 2048,
+  "model_type": "mixtral",
+  "num_attention_heads": 12,
+  "num_experts_per_tok": 2,
+  "num_hidden_layers": 10,
+  "num_key_value_heads": 4,
+  "num_local_experts": 2,
+  "output_router_logits": false,
+  "rms_norm_eps": 1e-6,
+  "rope_theta": 10000.0,
+  "router_aux_loss_coef": 0.001,
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.38.2",
+  "use_cache": true,
+  "vocab_size": 32002
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 32000,
+  "transformers_version": "4.38.2"
+}

license.txt

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special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
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+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

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tokenizer_config.json

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+{
+  "add_bos_token": false,
+  "add_eos_token": false,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32000": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32001": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "additional_special_tokens": [],
+  "bos_token": "<s>",
+  "chat_template": "{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "legacy": true,
+  "model_max_length": 2048,
+  "pad_token": "<s>",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}