Text Generation
Transformers
Safetensors
PyTorch
English
mistral
finetuned
quantized
4-bit precision
AWQ
instruct
conversational
text-generation-inference
finetune
chatml
Generated from Trainer
awq
Instructions to use solidrust/Senzu-7B-v0.1-DPO-AWQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use solidrust/Senzu-7B-v0.1-DPO-AWQ with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="solidrust/Senzu-7B-v0.1-DPO-AWQ")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("solidrust/Senzu-7B-v0.1-DPO-AWQ") model = AutoModelForCausalLM.from_pretrained("solidrust/Senzu-7B-v0.1-DPO-AWQ", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use solidrust/Senzu-7B-v0.1-DPO-AWQ with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "solidrust/Senzu-7B-v0.1-DPO-AWQ" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "solidrust/Senzu-7B-v0.1-DPO-AWQ", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/solidrust/Senzu-7B-v0.1-DPO-AWQ
- SGLang
How to use solidrust/Senzu-7B-v0.1-DPO-AWQ 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 "solidrust/Senzu-7B-v0.1-DPO-AWQ" \ --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": "solidrust/Senzu-7B-v0.1-DPO-AWQ", "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 "solidrust/Senzu-7B-v0.1-DPO-AWQ" \ --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": "solidrust/Senzu-7B-v0.1-DPO-AWQ", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use solidrust/Senzu-7B-v0.1-DPO-AWQ with Docker Model Runner:
docker model run hf.co/solidrust/Senzu-7B-v0.1-DPO-AWQ
Download special_tokens_map.json from solidrust/Senzu-7B-v0.1-DPO-AWQ: direct link, hf CLI and curl.
- Browser
- Download file 551 Bytes
-
https://huggingface.co/solidrust/Senzu-7B-v0.1-DPO-AWQ/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://solidrust/Senzu-7B-v0.1-DPO-AWQ/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/solidrust/Senzu-7B-v0.1-DPO-AWQ/resolve/main/special_tokens_map.json
551 Bytes
| { | |
| "bos_token": { | |
| "content": "<s>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "eos_token": { | |
| "content": "</s>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "pad_token": { | |
| "content": "</s>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "unk_token": { | |
| "content": "<unk>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| } | |
| } | |