Instructions to use OpenAssistant/stablelm-7b-sft-v7-epoch-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenAssistant/stablelm-7b-sft-v7-epoch-3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="OpenAssistant/stablelm-7b-sft-v7-epoch-3")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("OpenAssistant/stablelm-7b-sft-v7-epoch-3") model = AutoModelForCausalLM.from_pretrained("OpenAssistant/stablelm-7b-sft-v7-epoch-3") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use OpenAssistant/stablelm-7b-sft-v7-epoch-3 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "OpenAssistant/stablelm-7b-sft-v7-epoch-3" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OpenAssistant/stablelm-7b-sft-v7-epoch-3", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/OpenAssistant/stablelm-7b-sft-v7-epoch-3
- SGLang
How to use OpenAssistant/stablelm-7b-sft-v7-epoch-3 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 "OpenAssistant/stablelm-7b-sft-v7-epoch-3" \ --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": "OpenAssistant/stablelm-7b-sft-v7-epoch-3", "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 "OpenAssistant/stablelm-7b-sft-v7-epoch-3" \ --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": "OpenAssistant/stablelm-7b-sft-v7-epoch-3", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use OpenAssistant/stablelm-7b-sft-v7-epoch-3 with Docker Model Runner:
docker model run hf.co/OpenAssistant/stablelm-7b-sft-v7-epoch-3
Adding `safetensors` variant of this model
#11 opened over 1 year ago
by
SFconvertbot
Adding Evaluation Results
#10 opened over 2 years ago
by
leaderboard-pr-bot
[AUTOMATED] Model Memory Requirements
#9 opened over 2 years ago
by
model-sizer-bot
The model weights are not tied. Please use the `tie_weights` method before using the `infer_auto_device` function.
1
#8 opened almost 3 years ago
by
carlosmoises
GPTQ 4bit 128g
#7 opened about 3 years ago
by
pszemraj
3B Model
#6 opened about 3 years ago
by
aszfcxcgszdx
GGML f16, q4_0, q4_1, q4_2, q4_3
#4 opened about 3 years ago
by
oeathus
Can anyone make ggml 4bit q4_0 version?
3
#3 opened about 3 years ago
by
4eJIoBek