Text Generation
Transformers
Safetensors
English
mistral
instruct
finetune
chatml
gpt4
conversational
text-generation-inference
Instructions to use FPHam/Autolycus-Mistral_7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FPHam/Autolycus-Mistral_7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="FPHam/Autolycus-Mistral_7B") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("FPHam/Autolycus-Mistral_7B") model = AutoModelForCausalLM.from_pretrained("FPHam/Autolycus-Mistral_7B") 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]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use FPHam/Autolycus-Mistral_7B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "FPHam/Autolycus-Mistral_7B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "FPHam/Autolycus-Mistral_7B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/FPHam/Autolycus-Mistral_7B
- SGLang
How to use FPHam/Autolycus-Mistral_7B 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 "FPHam/Autolycus-Mistral_7B" \ --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": "FPHam/Autolycus-Mistral_7B", "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 "FPHam/Autolycus-Mistral_7B" \ --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": "FPHam/Autolycus-Mistral_7B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use FPHam/Autolycus-Mistral_7B with Docker Model Runner:
docker model run hf.co/FPHam/Autolycus-Mistral_7B
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language:
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license: apache-2.0
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model-index:
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- name: OpenAutolycus-2.5-Mistral-7B
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results: []
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model_creator: FPHam
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model_name: OpenAutolycus 2 Mistral 7B
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model_type: mistral
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prompt_template: '<|im_start|>system
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{system_message}<|im_end|>
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<|im_start|>user
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<|im_start|>assistant
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tags:
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- mistral
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- instruct
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- distillation
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Autolycus is son of Hermes.
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OpenAutolycus is a language refinement of OpenHermes with pushing
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license: apache-2.0
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language:
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tags:
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- mistral
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- instruct
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- distillation
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Autolycus is a son of Hermes.
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OpenAutolycus is a language refinement of OpenHermes with pushing its responses to more natural language.
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- Original model: [OpenHermes 2 Mistral 7B](https://huggingface.co/teknium/OpenHermes-2-Mistral-7B)
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