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+ ---
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+ language:
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+ - en
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+ license: apache-2.0
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+ datasets:
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+ - databricks/databricks-dolly-15k
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+ - Felladrin/ChatML-databricks-dolly-15k
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+ - euclaise/reddit-instruct-curated
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+ - Felladrin/ChatML-reddit-instruct-curated
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+ - THUDM/webglm-qa
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+ - Felladrin/ChatML-WebGLM-QA
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+ - starfishmedical/webGPT_x_dolly
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+ - Felladrin/ChatML-webGPT_x_dolly
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+ - LDJnr/Capybara
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+ - Felladrin/ChatML-Capybara
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+ - Open-Orca/SlimOrca-Dedup
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+ - Felladrin/ChatML-SlimOrca-Dedup
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+ - HuggingFaceH4/ultrachat_200k
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+ - Felladrin/ChatML-ultrachat_200k
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+ - nvidia/HelpSteer
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+ - Felladrin/ChatML-HelpSteer
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+ - sablo/oasst2_curated
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+ - Felladrin/ChatML-oasst2_curated
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+ - CohereForAI/aya_dataset
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+ - Felladrin/ChatML-aya_dataset
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+ - argilla/distilabel-capybara-dpo-7k-binarized
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+ - Felladrin/ChatML-distilabel-capybara-dpo-7k-binarized
28
+ - argilla/distilabel-intel-orca-dpo-pairs
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+ - Felladrin/ChatML-distilabel-intel-orca-dpo-pairs
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+ - argilla/ultrafeedback-binarized-preferences
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+ - Felladrin/ChatML-ultrafeedback-binarized-preferences
32
+ - sablo/oasst2_dpo_pairs_en
33
+ - Felladrin/ChatML-oasst2_dpo_pairs_en
34
+ - NeuralNovel/Neural-DPO
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+ - Felladrin/ChatML-Neural-DPO
36
+ base_model: Felladrin/Minueza-32M-Base
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+ pipeline_tag: text-generation
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+ widget:
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+ - messages:
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+ - role: system
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+ content:
42
+ You are a career counselor. The user will provide you with an individual
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+ looking for guidance in their professional life, and your task is to assist
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+ them in determining what careers they are most suited for based on their skills,
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+ interests, and experience. You should also conduct research into the various
46
+ options available, explain the job market trends in different industries, and
47
+ advice on which qualifications would be beneficial for pursuing particular fields.
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+ - role: user
49
+ content: Heya!
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+ - role: assistant
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+ content: Hi! How may I help you?
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+ - role: user
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+ content:
54
+ I am interested in developing a career in software engineering. What
55
+ would you recommend me to do?
56
+ - messages:
57
+ - role: system
58
+ content:
59
+ You are a highly knowledgeable assistant. Help the user as much as you
60
+ can.
61
+ - role: user
62
+ content: How can I become a healthier person?
63
+ - messages:
64
+ - role: system
65
+ content: You are a helpful assistant who gives creative responses.
66
+ - role: user
67
+ content: Write the specs of a game about mages in a fantasy world.
68
+ - messages:
69
+ - role: system
70
+ content: You are a helpful assistant who answers user's questions with details.
71
+ - role: user
72
+ content: Tell me about the pros and cons of social media.
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+ - messages:
74
+ - role: system
75
+ content:
76
+ You are a helpful assistant who answers user's questions with details
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+ and curiosity.
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+ - role: user
79
+ content: What are some potential applications for quantum computing?
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+ inference:
81
+ parameters:
82
+ max_new_tokens: 250
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+ do_sample: true
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+ temperature: 0.65
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+ top_p: 0.55
86
+ top_k: 35
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+ repetition_penalty: 1.176
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+ ---
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+
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+ # Minueza-32Mx2-Chat
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+
92
+ - Base model: [Felladrin/Minueza-32M-Base](https://huggingface.co/Felladrin/Minueza-32M-Base)
93
+ - Datasets used during SFT:
94
+ - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-databricks-dolly-15k)] [databricks/databricks-dolly-15k](https://huggingface.co/datasets/databricks/databricks-dolly-15k)
95
+ - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-reddit-instruct-curated)] [euclaise/reddit-instruct-curated](https://huggingface.co/datasets/euclaise/reddit-instruct-curated)
96
+ - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-WebGLM-QA)] [THUDM/webglm-qa](https://huggingface.co/datasets/THUDM/webglm-qa)
97
+ - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-webGPT_x_dolly)] [starfishmedical/webGPT_x_dolly](https://huggingface.co/datasets/starfishmedical/webGPT_x_dolly)
98
+ - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-Capybara)] [LDJnr/Capybara](https://huggingface.co/datasets/LDJnr/Capybara)
99
+ - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-SlimOrca-Dedup)] [Open-Orca/SlimOrca-Dedup](https://huggingface.co/datasets/Open-Orca/SlimOrca-Dedup)
100
+ - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-ultrachat_200k)] [HuggingFaceH4/ultrachat_200k](https://huggingface.co/datasets/HuggingFaceH4/ultrachat_200k)
101
+ - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-HelpSteer)] [nvidia/HelpSteer](https://huggingface.co/datasets/nvidia/HelpSteer)
102
+ - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-oasst2_curated)] [sablo/oasst2_curated](https://huggingface.co/datasets/sablo/oasst2_curated)
103
+ - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-aya_dataset)] [CohereForAI/aya_dataset](https://huggingface.co/datasets/CohereForAI/aya_dataset)
104
+ - Datasets used during DPO:
105
+ - [[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)
106
+ - [[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)
107
+ - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-ultrafeedback-binarized-preferences)] [argilla/ultrafeedback-binarized-preferences](https://huggingface.co/datasets/argilla/ultrafeedback-binarized-preferences)
108
+ - [[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)
109
+ - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-Neural-DPO)] [NeuralNovel/Neural-DPO](https://huggingface.co/datasets/NeuralNovel/Neural-DPO)
110
+ - License: [Apache License 2.0](https://huggingface.co/Felladrin/Minueza-32Mx2-Chat/resolve/main/license.txt)
111
+
112
+ ## Recommended Prompt Format
113
+
114
+ ```
115
+ <|im_start|>system
116
+ {system_message}<|im_end|>
117
+ <|im_start|>user
118
+ {user_message}<|im_end|>
119
+ <|im_start|>assistant
120
+ ```
121
+
122
+ ## Recommended Inference Parameters
123
+
124
+ ```yml
125
+ do_sample: true
126
+ temperature: 0.65
127
+ top_p: 0.55
128
+ top_k: 35
129
+ repetition_penalty: 1.176
130
+ ```
131
+
132
+ ## Usage Example
133
+
134
+ ```python
135
+ from transformers import pipeline
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+
137
+ generate = pipeline("text-generation", "Felladrin/Minueza-32Mx2-Chat")
138
+
139
+ messages = [
140
+ {
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+ "role": "system",
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+ "content": "You are a helpful assistant who answers the user's questions with details and curiosity.",
143
+ },
144
+ {
145
+ "role": "user",
146
+ "content": "What are some potential applications for quantum computing?",
147
+ },
148
+ ]
149
+
150
+ prompt = generate.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
151
+
152
+ output = generate(
153
+ prompt,
154
+ max_new_tokens=256,
155
+ do_sample=True,
156
+ temperature=0.65,
157
+ top_k=35,
158
+ top_p=0.55,
159
+ repetition_penalty=1.176,
160
+ )
161
+
162
+ print(output[0]["generated_text"])
163
+ ```
164
+
165
+ ## How it was trained
166
+
167
+ 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:
168
+
169
+ For Supervised Fine-Tuning:
170
+
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+ | Hyperparameter | Value |
172
+ | :--------------------- | :-------------------------------------------- |
173
+ | Learning rate | 2e-6 |
174
+ | Total train batch size | 16 |
175
+ | Max. sequence length | 2048 |
176
+ | Weight decay | 0.01 |
177
+ | Warmup ratio | 0.1 |
178
+ | Optimizer | Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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+ | Scheduler | cosine |
180
+ | Seed | 42 |
181
+ | Neftune Noise Alpha | 5 |
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+
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+ For Direct Preference Optimization:
184
+
185
+ | Hyperparameter | Value |
186
+ | :--------------------- | :---- |
187
+ | Learning rate | 5e-7 |
188
+ | Total train batch size | 16 |
189
+ | Max. length | 1024 |
190
+ | Max. prompt length | 512 |
191
+ | Max. steps | 200 |
192
+ | Weight decay | 0 |
193
+ | Warmup ratio | 0.1 |
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+ | Beta | 0.1 |
added_tokens.json ADDED
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+ {
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+ "<|im_end|>": 32000,
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+ "<|im_start|>": 32001
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+ }
config.json ADDED
@@ -0,0 +1,27 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "architectures": ["MixtralForCausalLM"],
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+ "attention_dropout": 0.0,
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+ "bos_token_id": 1,
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+ "eos_token_id": 32000,
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+ "hidden_act": "silu",
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+ "hidden_size": 312,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 1092,
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+ "max_position_embeddings": 2048,
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+ "model_type": "mixtral",
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+ "num_attention_heads": 12,
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+ "num_experts_per_tok": 2,
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+ "num_hidden_layers": 10,
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+ "num_key_value_heads": 4,
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+ "num_local_experts": 2,
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+ "output_router_logits": false,
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+ "rms_norm_eps": 1e-6,
19
+ "rope_theta": 10000.0,
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+ "router_aux_loss_coef": 0.001,
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+ "sliding_window": null,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "float32",
24
+ "transformers_version": "4.38.2",
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+ "use_cache": true,
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+ "vocab_size": 32002
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+ }
generation_config.json ADDED
@@ -0,0 +1,6 @@
 
 
 
 
 
 
 
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+ {
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+ "_from_model_config": true,
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+ "bos_token_id": 1,
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+ "eos_token_id": 32000,
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+ "transformers_version": "4.38.2"
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+ }
license.txt ADDED
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