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@@ -10,17 +10,17 @@ pipeline_tag: text-generation
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  # 🌿 Shurale7B-v1: Narrative based chit-chat model
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  Developed
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- by [@BobaZooba](https://www.linkedin.com/in/boriszubarev/) | [CV](https://docs.google.com/document/d/1BhFvIHQ1mpm81P-n2A-lhNac-U2wOGc6F2uS9gKvk88/edit?usp=sharing) | [LinkedIn](https://www.linkedin.com/in/boriszubarev/) | [[email protected]](mailto:[email protected])
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- [<img src="https://cdn-uploads.huggingface.co/production/uploads/6074d5f1134c000d1ae10d42/JudU3rrPP5i87CfwINANO.png" alt="Powered by X—LLM" width="175" height="32"/>](https://github.com/KompleteAI/xllm)
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  # 🪄 About
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  Model based on [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)
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- [GitHub Repo](https://github.com/KompleteAI/shurale) | [Detailed step-by-step guide how to train this model](https://github.com/KompleteAI/shurale/blob/main/STEP-BY-STEP-GUIDE.md)
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- [<img src="https://cdn-uploads.huggingface.co/production/uploads/6074d5f1134c000d1ae10d42/4y7RfOdhxvh1Tim99uLkW.png" alt="Chat with Shurale" width="120" height="40"/>](https://t.me/ShuraleAIBot)
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  | **HuggingFace Hub** | **7B** | **7B-GPTQ** |
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  |---------------------|---------------------------------------------------------------|-------------------------------------------------------------|
@@ -42,7 +42,7 @@ Model based on [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.
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  > Shurale [/ʃʊrɑˈlʲe/] is a forest spirit in Bashkir and Tatar mythology.
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- [Do you want models as cool as this one?](https://huggingface.co/KompleteAI/Shurale7B-v1#🚀-call-to-action)
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  </div>
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@@ -128,7 +128,15 @@ don't you dare let me down!
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  # 🔧 How to use
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- Recommended **top_p** for sampling: 0.9
 
 
 
 
 
 
 
 
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  ## Transformers
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  ```python
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  from transformers import AutoTokenizer, AutoModelForCausalLM
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- tokenizer = AutoTokenizer.from_pretrained("KompleteAI/Shurale7B-v1")
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- model = AutoModelForCausalLM.from_pretrained("KompleteAI/Shurale7B-v1")
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  ```
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  2. Run generation
@@ -172,11 +180,11 @@ https://github.com/huggingface/text-generation-inference#get-started
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  ### Docker
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  ```bash
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- model=KompleteAI/Shurale7B-v1
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  volume=$PWD/data
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  version=1.1.0 # please make sure you are using latest or stable version (>= 1.1.0)
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- docker run --gpus all --shm-size 1g -p 8080:80 -v \
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  $volume:/data ghcr.io/huggingface/text-generation-inference:$version \
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  --model-id $model --max-batch-prefill-tokens 2048 --dtype bfloat16
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  ```
@@ -191,7 +199,7 @@ https://www.runpod.io/console/gpu-cloud
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  | Field | Value |
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  |-------------------|-----------------------------------------------------------------------------------------------------------------------------|
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  | Container Image | ghcr.io/huggingface/text-generation-inference:1.1.0 |
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- | Docker Command | --model-id KompleteAI/Shurale7B-v1 --num-shard 1 --port 8081 --max-batch-prefill-tokens 2048 --dtype bfloat16 --json-output |
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  | Container Disk | 5 |
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  | Volume Disk | 15 |
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  | Volume Mount Path | /data |
@@ -252,7 +260,7 @@ print(text)
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  # 🚄 Training Process
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- [<img src="https://cdn-uploads.huggingface.co/production/uploads/6074d5f1134c000d1ae10d42/JudU3rrPP5i87CfwINANO.png" alt="Powered by X—LLM" width="175" height="32"/>](https://github.com/KompleteAI/xllm)
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  ## Dataset
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  # 📋 Dialog examples
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  <details>
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  <summary>Example #1</summary>
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  If this model proves successful, I plan to implement an algorithm similar to DeepMind's
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  ReST ([link](https://arxiv.org/pdf/2308.08998.pdf)). The mentioned work has great potential but has a number of
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  shortcomings, which I've managed to address in my approach.
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-
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- ---
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-
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- # 🚀 Call to action
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-
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- **Looking for an expert in modern LLMs?** I've got the experience you need. I'll guide you through every step,
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- fine-tuning everything from data collection to model training and improvement.
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-
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- **Why me?** Well, with six years of experience in deep learning R&D projects, I've mastered a range of roles - from
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- leading a team to rolling up my sleeves as an engineer. I've built and improved products from scratch and I'm keen to do
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- the same for you.
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-
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- **Worried about your team?** Don't be. With four years as a lecturer at Russia’s best university, I can equip them with
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- the skills they need to succeed.
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-
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- **Want to know more?** Check
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- out [my CV](https://docs.google.com/document/d/1BhFvIHQ1mpm81P-n2A-lhNac-U2wOGc6F2uS9gKvk88/edit?usp=sharing), [LinkedIn](https://www.linkedin.com/in/boriszubarev/),
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- and [past projects](https://komplete.framer.ai/cases) for the full scoop.
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-
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- **Ready to start?** Let's arrange a free intro meeting. I'll outline the resources we'll need to make your project a
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- success.
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- [Contact me form](https://komplete.framer.ai/#contact)
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-
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- If you're an engineer, I'd appreciate it if you could pass
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- along [my LinkedIn](https://www.linkedin.com/in/boriszubarev/) or [website](https://komplete.framer.ai/) to your
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- manager.
 
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  # 🌿 Shurale7B-v1: Narrative based chit-chat model
11
 
12
  Developed
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+ by [@BobaZooba](https://t.me/BobaZooba) | [CV](https://docs.google.com/document/d/1BhFvIHQ1mpm81P-n2A-lhNac-U2wOGc6F2uS9gKvk88/edit?usp=sharing) | [LinkedIn](https://www.linkedin.com/in/boriszubarev/) | [[email protected]](mailto:[email protected])
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+ [<img src="https://cdn-uploads.huggingface.co/production/uploads/6074d5f1134c000d1ae10d42/JudU3rrPP5i87CfwINANO.png" alt="Powered by X—LLM" width="175" height="32"/>](https://github.com/BobaZooba/xllm)
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  # 🪄 About
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  Model based on [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)
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+ [GitHub Repo](https://github.com/BobaZooba/shurale) | [Detailed step-by-step guide how to train this model](https://github.com/BobaZooba/shurale/blob/main/STEP-BY-STEP-GUIDE.md)
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+ [<img src="https://cdn-uploads.huggingface.co/production/uploads/6074d5f1134c000d1ae10d42/4y7RfOdhxvh1Tim99uLkW.png" alt="Chat with Shurale" width="120" height="40"/>](https://t.me/TaleQuestBot)
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  | **HuggingFace Hub** | **7B** | **7B-GPTQ** |
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  |---------------------|---------------------------------------------------------------|-------------------------------------------------------------|
 
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  > Shurale [/ʃʊrɑˈlʲe/] is a forest spirit in Bashkir and Tatar mythology.
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45
+ [Do you want models as cool as this one?](https://www.linkedin.com/in/boriszubarev/)
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  </div>
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  # 🔧 How to use
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+ Recommended generation parameters for sampling:
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+
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+ | Param | Value |
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+ |-----------|-------|
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+ | top_p | 0.75 |
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+ | typical_p | 0.95 |
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+ | top_k | 50 |
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+ | temperature | 0.75 |
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+ | repetition_penalty | 1.05 |
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  ## Transformers
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  ```python
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  from transformers import AutoTokenizer, AutoModelForCausalLM
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+ tokenizer = AutoTokenizer.from_pretrained("BobaZooba/Shurale7B-v1")
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+ model = AutoModelForCausalLM.from_pretrained("BobaZooba/Shurale7B-v1")
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  ```
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  2. Run generation
 
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  ### Docker
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  ```bash
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+ model=BobaZooba/Shurale7B-v1
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  volume=$PWD/data
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  version=1.1.0 # please make sure you are using latest or stable version (>= 1.1.0)
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+ docker run --gpus all --shm-size 1g -p 8081:80 -v \
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  $volume:/data ghcr.io/huggingface/text-generation-inference:$version \
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  --model-id $model --max-batch-prefill-tokens 2048 --dtype bfloat16
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  ```
 
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  | Field | Value |
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  |-------------------|-----------------------------------------------------------------------------------------------------------------------------|
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  | Container Image | ghcr.io/huggingface/text-generation-inference:1.1.0 |
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+ | Docker Command | --model-id BobaZooba/Shurale7B-v1 --num-shard 1 --port 8081 --max-batch-prefill-tokens 2048 --dtype bfloat16 --json-output |
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  | Container Disk | 5 |
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  | Volume Disk | 15 |
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  | Volume Mount Path | /data |
 
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  # 🚄 Training Process
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+ [<img src="https://cdn-uploads.huggingface.co/production/uploads/6074d5f1134c000d1ae10d42/JudU3rrPP5i87CfwINANO.png" alt="Powered by X—LLM" width="175" height="32"/>](https://github.com/BobaZooba/xllm)
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  ## Dataset
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  # 📋 Dialog examples
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+ ## Tale Quest
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+
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+ `Tale Quest` is my personal project which was built using `xllm` and `Shurale`. It's an interactive text-based game
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+ in `Telegram` with dynamic AI characters, offering infinite scenarios
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+
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+ You will get into exciting journeys and complete fascinating quests. Chat
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+ with `George Orwell`, `Tech Entrepreneur`, `Young Wizard`, `Noir Detective`, `Femme Fatale` and many more
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+
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+ Try it now: [https://t.me/talequestbot](https://t.me/PapayaAIBot?start=Z2g)
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+
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+ Default examples (not as interesting as in TaleQuest):
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+
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  <details>
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  <summary>Example #1</summary>
487
 
 
609
  If this model proves successful, I plan to implement an algorithm similar to DeepMind's
610
  ReST ([link](https://arxiv.org/pdf/2308.08998.pdf)). The mentioned work has great potential but has a number of
611
  shortcomings, which I've managed to address in my approach.