Text Generation
Safetensors
English
Chinese
qwen3
fine-tuned
custom
conversational
custom_code
4-bit precision
gptq
Instructions to use eibrahim/do-xrepo-model-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps Settings
- vLLM
How to use eibrahim/do-xrepo-model-3 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "eibrahim/do-xrepo-model-3" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "eibrahim/do-xrepo-model-3", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/eibrahim/do-xrepo-model-3
- SGLang
How to use eibrahim/do-xrepo-model-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 "eibrahim/do-xrepo-model-3" \ --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": "eibrahim/do-xrepo-model-3", "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 "eibrahim/do-xrepo-model-3" \ --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": "eibrahim/do-xrepo-model-3", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use eibrahim/do-xrepo-model-3 with Docker Model Runner:
docker model run hf.co/eibrahim/do-xrepo-model-3
Configuration Parsing Warning:In UNKNOWN_FILENAME: "auto_map.AutoTokenizer" must be a string
Qwen3-1.5B-Finetuned
A fine-tuned version of Qwen3-1.5B optimized for enterprise workloads.
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("do-import-test/qwen3-finetuned-v1")
tokenizer = AutoTokenizer.from_pretrained("do-import-test/qwen3-finetuned-v1")
Training Details
- Base model: Qwen/Qwen3-1.5B
- Fine-tuning method: LoRA
- Dataset: Custom enterprise corpus
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