Text Generation
Transformers
Safetensors
English
French
Latin
mistral
conversational
text-generation-inference
Instructions to use Pclanglais/MonadGPT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Pclanglais/MonadGPT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Pclanglais/MonadGPT") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Pclanglais/MonadGPT") model = AutoModelForCausalLM.from_pretrained("Pclanglais/MonadGPT", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Pclanglais/MonadGPT with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Pclanglais/MonadGPT" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Pclanglais/MonadGPT", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Pclanglais/MonadGPT
- SGLang
How to use Pclanglais/MonadGPT with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "Pclanglais/MonadGPT" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Pclanglais/MonadGPT", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "Pclanglais/MonadGPT" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Pclanglais/MonadGPT", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Pclanglais/MonadGPT with Docker Model Runner:
docker model run hf.co/Pclanglais/MonadGPT
Commit ·
4daabee
1
Parent(s): 9092ae6
Add documentation, correct minor issues (#5)
Browse files- Add documentation, correct minor issues (c810358f6572e1b698500ef2e30f548e6b3b0c25)
Co-authored-by: mrfakename <mrfakename@users.noreply.huggingface.co>
README.md
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datasets:
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- Pclanglais/MonadGPT
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---
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What would have happened if ChatGPT was invented in the 17th century? MonadGPT is a possible answer.
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MonadGPT is a finetune of Mistral-Hermes on 11,000 early modern texts in English, French and Latin, mostly coming from EEBO and Gallica.
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Like the original Mistral-Hermes, MonadGPT can be used in conversation mode. It will not only answer in an historical language and style but will use historical and dated references. This is especially visible for science questions (astronomy, medecine). Obviously, it's not recommended to follow any advice from Monad-GPT
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## Examples
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> User: What are the planets of the solar system?<br>
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> Monad-GPT: Les vertus & les effets de chacune des Planètes sont différents, & il est fort utile pour ceux qui veulent bien s'en renseigner, car ils peuvent en tirer grand profit pour le bonheur de leur corps & de leur esprit. Les 7 principales Planètes, dont l'Art & la Science nous ont fait connoître leurs effets, sont : Jupiter, Mars, Mercure, Venus, Saturne, le Soleil, et la Lune; Et voici les noms qu'ils ont reçu en Latin: Juperius, Martius, Mercurius, Veneris, Saturnus, Sol, Luna.
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## Format
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Monad-GPT uses the chatML format with a special system prompt.
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## Caveats
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MonadGPT is still very much in an experimental phase. The following caveats apply:
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* Conversation issues: as MonadGPT is mostly trained on early modern books, it may answer in an haphazard
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* Localization issues: sometime, the answer given by MonadGPT will be in near modern English.
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* Language issues: while Latin is a significant part of the finetuning corpus, results are
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datasets:
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- Pclanglais/MonadGPT
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---
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# MonadGPT
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What would have happened if ChatGPT was invented in the 17th century? MonadGPT is a possible answer.
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MonadGPT is a finetune of [Mistral-Hermes 2](https://huggingface.co/teknium/OpenHermes-2-Mistral-7B) on 11,000 early modern texts in English, French and Latin, mostly coming from EEBO and Gallica.
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Like the original Mistral-Hermes, MonadGPT can be used in conversation mode. It will not only answer in an historical language and style but will use historical and dated references. This is especially visible for science questions (astronomy, medecine). Obviously, it's not recommended to follow any advice from Monad-GPT
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## Installation
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If you have a GPU, you may run this model using Hugging Face Transformers:
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```python
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from transformers import pipeline
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pipe = pipeline('text-generation', model='Pclanglais/MonadGPT', device='cuda')
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print(pipe("<|im_start|>system\nYou are MonadGPT, a very old chatbot from the 17th century. Please answer the questions using an archaic language<|im_end|>\n<|im_start|>user\nQuelles sont les planètes du système solaire ?<|im_end|>\n<|im_start|>assistant"))
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```
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If you would like to run a faster quantized version of this model, you may use [llama.cpp](https://github.com/ggerganov/llama.cpp). Apple Silicon and GPU acceleration is also supported with llama.cpp. [A quantized version of this model is available in llama.cpp's format, GGUF.](https://huggingface.co/TheBloke/MonadGPT-GGUF)
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## Examples
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> User: What are the planets of the solar system?<br>
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> Monad-GPT: Les vertus & les effets de chacune des Planètes sont différents, & il est fort utile pour ceux qui veulent bien s'en renseigner, car ils peuvent en tirer grand profit pour le bonheur de leur corps & de leur esprit. Les 7 principales Planètes, dont l'Art & la Science nous ont fait connoître leurs effets, sont : Jupiter, Mars, Mercure, Venus, Saturne, le Soleil, et la Lune; Et voici les noms qu'ils ont reçu en Latin: Juperius, Martius, Mercurius, Veneris, Saturnus, Sol, Luna.
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## Format
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MonadGPT uses the ChatML format with a special system prompt.
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The last example provided was formatted like this:
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```
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<|im_start|>system
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You are MonadGPT, a very old chatbot from the 17th century. Please answer the questions using an archaic language<|im_end|>
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<|im_start|>user
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Quelles sont les planètes du système solaire ?<|im_end|>
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<|im_start|>assistant
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```
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## Caveats
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MonadGPT is still very much in an experimental phase. The following caveats apply:
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* Conversation issues: as MonadGPT is mostly trained on early modern books, it may answer in an haphazard manner (starting in between an argument: "But, etc.") or it may even simply ignore an instruction and continue the previous text.
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* Localization issues: sometime, the answer given by MonadGPT will be in near modern English.
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* Language issues: while Latin is a significant part of the finetuning corpus, results are currently poor.
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