Instructions to use DaertML/LLaMA-Turrera-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DaertML/LLaMA-Turrera-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="DaertML/LLaMA-Turrera-7B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("DaertML/LLaMA-Turrera-7B") model = AutoModelForCausalLM.from_pretrained("DaertML/LLaMA-Turrera-7B") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use DaertML/LLaMA-Turrera-7B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "DaertML/LLaMA-Turrera-7B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DaertML/LLaMA-Turrera-7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/DaertML/LLaMA-Turrera-7B
- SGLang
How to use DaertML/LLaMA-Turrera-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 "DaertML/LLaMA-Turrera-7B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DaertML/LLaMA-Turrera-7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "DaertML/LLaMA-Turrera-7B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DaertML/LLaMA-Turrera-7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use DaertML/LLaMA-Turrera-7B with Docker Model Runner:
docker model run hf.co/DaertML/LLaMA-Turrera-7B
Update README.md
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README.md
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This model has been trained with the "turras" of "El Turrero", which can be found at: https://turrero.vercel.app/
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The credits of the "turras": https://twitter.com/Recuenco
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The credits of the sysadmin of the site: https://twitter.com/k4rliky
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With the objective to provide a true fine tuning of an LLM, and get beyond the capabilities of the GPTs, this model has been trained. You can also find a GPT that uses the content of the "turras" to chat with the user at:
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https://chat.openai.com/g/g-nam1wBUJm-turrero
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"La LLaMA Turrera" can produce "turras" in the same manner as "El Turrero" and provide further feedback from other "turras".
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The model has been trained with a non-profit intent, for fun and to serve as a base for further development.
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With the objective to learn about AI alignment, further versions of this model will be trained that attempt to avoid malicious usage from the users.
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The model is meant to be used with HuggingFace transformers API in Python, a version for LLaMA.cpp is under evaluation.
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