How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "jnjj/xddd"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "jnjj/xddd",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'
Use Docker
docker model run hf.co/jnjj/xddd
Quick Links

xddd

Este repositorio incluye:

  • hghghgkskdmskdms/xddd con fusi贸n completa de layers en 1 (sin eliminaci贸n de originales)
  • Fusi贸n de todos los tensores en un 煤nico vector continuo
  • Eliminaci贸n de bias y desactivaci贸n de censura
  • Configuraci贸n de generaci贸n: do_sample=True, temp=0.7, top_p=0.9, repetition_penalty=1.2, no_repeat_ngram_size=3
  • Funciones de decodificaci贸n de tokens, par谩metros, respuestas, layers, neuronas, tensores, arquitectura y tensor fusionado
  • max_position_embeddings: 8000
  • torch_dtype: float32
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("jnjj/xddd", torch_dtype="float32", trust_remote_code=True)
Downloads last month
9
Safetensors
Model size
0.5B params
Tensor type
F32
Inference Providers NEW
This model isn't deployed by any Inference Provider. 馃檵 Ask for provider support