Text Generation
Transformers
Safetensors
English
llama
text-generation-inference
unsloth
trl
sft
4-bit precision
bitsandbytes
Instructions to use student-abdullah/model_4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use student-abdullah/model_4bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="student-abdullah/model_4bit")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("student-abdullah/model_4bit") model = AutoModelForCausalLM.from_pretrained("student-abdullah/model_4bit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use student-abdullah/model_4bit with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "student-abdullah/model_4bit" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "student-abdullah/model_4bit", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/student-abdullah/model_4bit
- SGLang
How to use student-abdullah/model_4bit 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 "student-abdullah/model_4bit" \ --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": "student-abdullah/model_4bit", "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 "student-abdullah/model_4bit" \ --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": "student-abdullah/model_4bit", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Unsloth Desktop
- Docker Model Runner
How to use student-abdullah/model_4bit with Docker Model Runner:
docker model run hf.co/student-abdullah/model_4bit
Download generation_config.json from student-abdullah/model_4bit: direct link, hf CLI and curl.
- Browser
- Download file 230 Bytes
-
https://huggingface.co/student-abdullah/model_4bit/resolve/main/generation_config.json
- Command line
-
hf download hf://student-abdullah/model_4bit/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/student-abdullah/model_4bit/resolve/main/generation_config.json
230 Bytes
| { | |
| "_from_model_config": true, | |
| "bos_token_id": 128000, | |
| "do_sample": true, | |
| "eos_token_id": 128001, | |
| "max_length": 131072, | |
| "pad_token_id": 128004, | |
| "temperature": 0.6, | |
| "top_p": 0.9, | |
| "transformers_version": "4.44.2" | |
| } | |