初始化项目，由ModelHub XC社区提供模型

Model: TroyDoesAI/MermaidMistral
Source: Original Platform

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README.md

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+---
+license: apache-2.0
+---
+
+Posted here first: https://www.reddit.com/r/Oobabooga/comments/192qb2c/mermaidmistral_a_work_in_progress_model_for_flow/
+
+It's kinda barely under 16GB in full precision,
+you can give it a try using  ![Google Colab Notebook](https://github.com/Troys-Code/AI_For_Free/blob/main/MermaidMistral_Colab_TextGen_GPU.ipynb)
+I threw this together but be warned it will OOM on long context due to Free Tier being limited to 15GB VRAM.
+
+### Introduction:
+
+Introducing MermaidMistral, a powerful yet compact 7-billion-parameter language model adept at Python code understanding and crafting engaging story flow maps. Trained on a meticulously hand curated dataset of 478 diverse Python examples and hand crafted mermaid flow maps utilizing https://mermaid.live, this model goes beyond its size to deliver exceptional performance in code understanding and story visualization.
+
+### Key Features:
+MermaidMistral is not a "Chatty Kathy" and should only respond with a mermaid code block with a flow diagram in mermaid js syntax and nothing more.
+
+**1. Code Understanding:**
+- Grasps Python intricacies with finesse.
+- Generates clear and accurate Mermaid Diagram Flow Charts.
+- Ideal for developers seeking visual representations of their code's logic.
+
+**2. Storytelling Capabilities:**
+- Converts narrative inputs into captivating Mermaid Diagrams.
+- Maps character interactions, plot developments, and narrative arcs effortlessly.
+
+**3. Unmatched Performance:**
+- Surpasses larger models, like GPT-4, in generating well-organized and detailed Mermaid Diagrams for story flows.
+
+**4. Training Insights:**
+- Trained on a 478 Python examples for just under three epochs on a single RTX 3090 following batch size equal to 1, known as stochastic gradient descent.
+- Exhibited emergent properties in story-to-flow map translations.
+- Adaptable and efficient in resource utilization
+- Due to hardware constraints this fine tune has a token limit of 2048.
+
+1. Mermaid Mistral Generation 1:
+   ![Mermaid Mistral Generation 1](https://cdn.discordapp.com/attachments/1022059414280228875/1194088817284612178/MermaidMistral_Generation1.png?ex=65af14df&is=659c9fdf&hm=dc1b8ddeb658de80c1646838fbd3c15a46a1d8efefec2b609a1bb48aaa238174&)
+
+2. Mermaid Mistral Generation 2:
+   ![Mermaid Mistral Generation 2](https://cdn.discordapp.com/attachments/1022059414280228875/1194088816416399462/MermaidMistral_Generation2.png?ex=65af14de&is=659c9fde&hm=c259ee6ad27824a0b932a936699d276d5f1ffd0418ac608de6cd96784c46aba1&)
+
+3. ChatGPT Generation:
+   ![ChatGPT Generation](https://cdn.discordapp.com/attachments/1022059414280228875/1194088816823242812/ChatGPT_Generation1.png?ex=65af14df&is=659c9fdf&hm=b5e2c75286ea7a1313ae455402e14cf2bb7e82c5fb66d92acc542909cf2a6352&)
+
+### Collaboration:
+
+MermaidMistral is open to collaboration to further strengthen its capabilities. The dataset, formatted in Alpaca, provides a unique foundation for understanding Python intricacies. If you're interested in contributing or collaborating to enhance the model's performance, feel free to reach out to [troydoesai@gmail.com](mailto:troydoesai@gmail.com). Your expertise could play a pivotal role in refining MermaidMistral.
+
+### Example Use Cases:
+
+**1. Code Documentation:**
+- Developers can use MermaidMistral to automatically generate visual flow charts from their Python code, aiding in documentation and code understanding.
+
+**2. Storyboarding:**
+- Storytellers and writers can input their narrative and receive visually appealing Mermaid Diagrams, offering a structured overview of character interactions and plot progression.
+
+**3. Project Planning:**
+- Project managers can leverage MermaidMistral to create visual project flow maps, facilitating effective communication and planning among team members.
+
+**4. Learning Python:**
+- Students and beginners can use MermaidMistral to visually understand Python code structures, enhancing their learning experience.
+
+**5. Game Design:**
+- Game developers can utilize MermaidMistral for visualizing game storylines, ensuring a coherent narrative structure and character development.
+
+### Proof of Concept:
+
+MermaidMistral proves that innovation thrives in compact packages, delivering exceptional performance across diverse applications. Its adaptability and efficiency showcase the potential for groundbreaking results even in resource-constrained environments.
+
+These mermaid codeblocks can be converted directly into images using mermaid cli tool found here: https://github.com/mermaid-js/mermaid-cli
+
+I plan to release my working proof of concept VSCode Extension that currently displays the ```Live Flow Map``` every time a user stops typing for more than 10 seconds.
+
+Stay tuned.
+ 
+### Example Story -> Flow
+https://chat.openai.com/share/e3163857-981b-4968-b2db-98ad869c9259
+
+### Insights on how to get best results
+# For best results use full precision using one of the 3 different instruction types:
+
+- "instruction": "Create the mermaid diagram for the following code:",
+- "instruction": "Create the mermaid diagram for the following story:",
+- "instruction": "Create the mermaid diagram for the following:",

config.json

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+{
+  "_name_or_path": ".\\MermaidMistral",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
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+  "model_type": "mistral",
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+  "rms_norm_eps": 1e-05,
+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.37.2",
+  "use_cache": true,
+  "vocab_size": 32000
+}

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+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "transformers_version": "4.37.2"
+}

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special_tokens_map.json

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+{
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+    "<s>",
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+  ],
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+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+  "pad_token": {
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+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+      "special": true
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+      "single_word": false,
+      "special": true
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+  "additional_special_tokens": [
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+  "bos_token": "<s>",
+  "chat_template": "{% for message in messages %}{{bos_token + message['role'] + '\n' + message['content'] + eos_token + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ bos_token + 'assistant\n' }}{% endif %}",
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+  "eos_token": "</s>",
+  "legacy": true,
+  "model_max_length": 8192,
+  "pad_token": "</s>",
+  "padding_side": "left",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "split_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": true
+}