Text Generation
Transformers
Safetensors
mistral
Merge
mergekit
lazymergekit
liminerity/Omningotex-7b-slerp
eren23/merged-dpo-binarized-NeutrixOmnibe-7B
Eval Results (legacy)
text-generation-inference
Instructions to use paulml/DPOB-INMTOB-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use paulml/DPOB-INMTOB-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="paulml/DPOB-INMTOB-7B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("paulml/DPOB-INMTOB-7B") model = AutoModelForCausalLM.from_pretrained("paulml/DPOB-INMTOB-7B") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use paulml/DPOB-INMTOB-7B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "paulml/DPOB-INMTOB-7B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "paulml/DPOB-INMTOB-7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/paulml/DPOB-INMTOB-7B
- SGLang
How to use paulml/DPOB-INMTOB-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 "paulml/DPOB-INMTOB-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": "paulml/DPOB-INMTOB-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 "paulml/DPOB-INMTOB-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": "paulml/DPOB-INMTOB-7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use paulml/DPOB-INMTOB-7B with Docker Model Runner:
docker model run hf.co/paulml/DPOB-INMTOB-7B
Great model
#4
by RedLeader721 - opened
Just wanted to express some support for this model. It still has the highest average rating on the leaderboards for its inference speed, which is 120 tokens/s on my RTX 3090. Keep it up!
Just wanted to express some support for this model. It still has the highest average rating on the leaderboards for its inference speed, which is 120 tokens/s on my RTX 3090. Keep it up!
Thanks a lot! What leaderboard are you talking about?