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Parent(s):
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Browse files- .gitattributes +35 -0
- README.md +194 -0
- added_tokens.json +4 -0
- config.json +27 -0
- generation_config.json +6 -0
- license.txt +201 -0
- model.safetensors +3 -0
- special_tokens_map.json +30 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +59 -0
.gitattributes
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README.md
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1 |
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---
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2 |
+
language:
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- en
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+
license: apache-2.0
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5 |
+
datasets:
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6 |
+
- databricks/databricks-dolly-15k
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7 |
+
- Felladrin/ChatML-databricks-dolly-15k
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8 |
+
- euclaise/reddit-instruct-curated
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9 |
+
- Felladrin/ChatML-reddit-instruct-curated
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10 |
+
- THUDM/webglm-qa
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11 |
+
- Felladrin/ChatML-WebGLM-QA
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12 |
+
- starfishmedical/webGPT_x_dolly
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13 |
+
- Felladrin/ChatML-webGPT_x_dolly
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14 |
+
- LDJnr/Capybara
|
15 |
+
- Felladrin/ChatML-Capybara
|
16 |
+
- Open-Orca/SlimOrca-Dedup
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17 |
+
- Felladrin/ChatML-SlimOrca-Dedup
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18 |
+
- HuggingFaceH4/ultrachat_200k
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19 |
+
- Felladrin/ChatML-ultrachat_200k
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20 |
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- nvidia/HelpSteer
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21 |
+
- Felladrin/ChatML-HelpSteer
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22 |
+
- sablo/oasst2_curated
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23 |
+
- Felladrin/ChatML-oasst2_curated
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24 |
+
- CohereForAI/aya_dataset
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25 |
+
- Felladrin/ChatML-aya_dataset
|
26 |
+
- argilla/distilabel-capybara-dpo-7k-binarized
|
27 |
+
- Felladrin/ChatML-distilabel-capybara-dpo-7k-binarized
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28 |
+
- argilla/distilabel-intel-orca-dpo-pairs
|
29 |
+
- Felladrin/ChatML-distilabel-intel-orca-dpo-pairs
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30 |
+
- argilla/ultrafeedback-binarized-preferences
|
31 |
+
- Felladrin/ChatML-ultrafeedback-binarized-preferences
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32 |
+
- sablo/oasst2_dpo_pairs_en
|
33 |
+
- Felladrin/ChatML-oasst2_dpo_pairs_en
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34 |
+
- NeuralNovel/Neural-DPO
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35 |
+
- Felladrin/ChatML-Neural-DPO
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36 |
+
base_model: Felladrin/Minueza-32M-Base
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37 |
+
pipeline_tag: text-generation
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38 |
+
widget:
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39 |
+
- messages:
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40 |
+
- role: system
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41 |
+
content:
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42 |
+
You are a career counselor. The user will provide you with an individual
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43 |
+
looking for guidance in their professional life, and your task is to assist
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44 |
+
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
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46 |
+
options available, explain the job market trends in different industries, and
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+
advice on which qualifications would be beneficial for pursuing particular fields.
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48 |
+
- role: user
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+
content: Heya!
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+
- role: assistant
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content: Hi! How may I help you?
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52 |
+
- role: user
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content:
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+
I am interested in developing a career in software engineering. What
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55 |
+
would you recommend me to do?
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56 |
+
- messages:
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57 |
+
- role: system
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58 |
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content:
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59 |
+
You are a highly knowledgeable assistant. Help the user as much as you
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can.
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61 |
+
- role: user
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62 |
+
content: How can I become a healthier person?
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63 |
+
- messages:
|
64 |
+
- role: system
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65 |
+
content: You are a helpful assistant who gives creative responses.
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66 |
+
- role: user
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67 |
+
content: Write the specs of a game about mages in a fantasy world.
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68 |
+
- messages:
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69 |
+
- role: system
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70 |
+
content: You are a helpful assistant who answers user's questions with details.
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71 |
+
- role: user
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72 |
+
content: Tell me about the pros and cons of social media.
|
73 |
+
- messages:
|
74 |
+
- role: system
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75 |
+
content:
|
76 |
+
You are a helpful assistant who answers user's questions with details
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77 |
+
and curiosity.
|
78 |
+
- role: user
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79 |
+
content: What are some potential applications for quantum computing?
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80 |
+
inference:
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81 |
+
parameters:
|
82 |
+
max_new_tokens: 250
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83 |
+
do_sample: true
|
84 |
+
temperature: 0.65
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85 |
+
top_p: 0.55
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86 |
+
top_k: 35
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87 |
+
repetition_penalty: 1.176
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+
---
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89 |
+
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90 |
+
# Minueza-32Mx2-Chat
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91 |
+
|
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)
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109 |
+
- [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-Neural-DPO)] [NeuralNovel/Neural-DPO](https://huggingface.co/datasets/NeuralNovel/Neural-DPO)
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110 |
+
- License: [Apache License 2.0](https://huggingface.co/Felladrin/Minueza-32Mx2-Chat/resolve/main/license.txt)
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+
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## Recommended Prompt Format
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+
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```
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<|im_start|>system
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{system_message}<|im_end|>
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+
<|im_start|>user
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{user_message}<|im_end|>
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<|im_start|>assistant
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```
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+
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## Recommended Inference Parameters
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+
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+
```yml
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do_sample: true
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+
temperature: 0.65
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+
top_p: 0.55
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+
top_k: 35
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repetition_penalty: 1.176
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```
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+
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## Usage Example
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+
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```python
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from transformers import pipeline
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generate = pipeline("text-generation", "Felladrin/Minueza-32Mx2-Chat")
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+
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messages = [
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{
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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.",
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+
},
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{
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"role": "user",
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"content": "What are some potential applications for quantum computing?",
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},
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+
]
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+
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+
prompt = generate.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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+
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+
output = generate(
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prompt,
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+
max_new_tokens=256,
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+
do_sample=True,
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+
temperature=0.65,
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+
top_k=35,
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+
top_p=0.55,
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+
repetition_penalty=1.176,
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+
)
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+
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print(output[0]["generated_text"])
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+
```
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+
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+
## How it was trained
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+
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+
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:
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For Supervised Fine-Tuning:
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| Hyperparameter | Value |
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| :--------------------- | :-------------------------------------------- |
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| Learning rate | 2e-6 |
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+
| Total train batch size | 16 |
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+
| Max. sequence length | 2048 |
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+
| Weight decay | 0.01 |
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+
| Warmup ratio | 0.1 |
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| Optimizer | Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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179 |
+
| Scheduler | cosine |
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| Seed | 42 |
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| Neftune Noise Alpha | 5 |
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+
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+
For Direct Preference Optimization:
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184 |
+
|
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| Hyperparameter | Value |
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| :--------------------- | :---- |
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| Learning rate | 5e-7 |
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+
| Total train batch size | 16 |
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| Max. length | 1024 |
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| Max. prompt length | 512 |
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| Max. steps | 200 |
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+
| Weight decay | 0 |
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| Warmup ratio | 0.1 |
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| Beta | 0.1 |
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added_tokens.json
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{
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"<|im_end|>": 32000,
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"<|im_start|>": 32001
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}
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config.json
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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,
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19 |
+
"rope_theta": 10000.0,
|
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|
21 |
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|
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|
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|
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|
25 |
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"use_cache": true,
|
26 |
+
"vocab_size": 32002
|
27 |
+
}
|
generation_config.json
ADDED
@@ -0,0 +1,6 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
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"_from_model_config": true,
|
3 |
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"bos_token_id": 1,
|
4 |
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"eos_token_id": 32000,
|
5 |
+
"transformers_version": "4.38.2"
|
6 |
+
}
|
license.txt
ADDED
@@ -0,0 +1,201 @@
|
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|
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model.safetensors
ADDED
@@ -0,0 +1,3 @@
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special_tokens_map.json
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tokenizer.json
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tokenizer.model
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tokenizer_config.json
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40 |
+
"normalized": false,
|
41 |
+
"rstrip": false,
|
42 |
+
"single_word": false,
|
43 |
+
"special": true
|
44 |
+
}
|
45 |
+
},
|
46 |
+
"additional_special_tokens": [],
|
47 |
+
"bos_token": "<s>",
|
48 |
+
"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 %}",
|
49 |
+
"clean_up_tokenization_spaces": false,
|
50 |
+
"eos_token": "<|im_end|>",
|
51 |
+
"legacy": true,
|
52 |
+
"model_max_length": 2048,
|
53 |
+
"pad_token": "<s>",
|
54 |
+
"sp_model_kwargs": {},
|
55 |
+
"spaces_between_special_tokens": false,
|
56 |
+
"tokenizer_class": "LlamaTokenizer",
|
57 |
+
"unk_token": "<unk>",
|
58 |
+
"use_default_system_prompt": false
|
59 |
+
}
|