Text Generation
Transformers
PyTorch
Safetensors
PEFT
Turkish
English
Spanish
Generative AI
text-generation-inference
unsloth
medical
biology
code
space
conversational
Instructions to use Meforgers/Aixr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Meforgers/Aixr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Meforgers/Aixr") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Meforgers/Aixr", device_map="auto") - PEFT
How to use Meforgers/Aixr with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Meforgers/Aixr with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Meforgers/Aixr" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Meforgers/Aixr", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Meforgers/Aixr
- SGLang
How to use Meforgers/Aixr 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 "Meforgers/Aixr" \ --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": "Meforgers/Aixr", "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 "Meforgers/Aixr" \ --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": "Meforgers/Aixr", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Unsloth Desktop
- Docker Model Runner
How to use Meforgers/Aixr with Docker Model Runner:
docker model run hf.co/Meforgers/Aixr
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Verified signatureCan you use that LLM with that code; from unsloth import FastLanguageModel model, tokenizer = FastLanguageModel.from_pretrained( model_name = "Meforgers/Aixrav", max_seq_length = max_seq_length, dtype = dtype, load_in_4bit = load_in_4bit, ) FastLanguageModel.for_inference(model) inputs = tokenizer( [ alpaca_prompt.format( "Can u text me a basic code?", # instruction "", # input "", # output - leave this blank for generation! ) ], return_tensors = "pt").to("cuda") outputs = model.generate(**inputs, max_new_tokens = 64, use_cache = True) tokenizer.batch_decode(outputs)599bd45 -
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