Text Generation
Transformers
Safetensors
Arabic
qwen
llama-factory
lora
arabic
question-answering
instruction-tuning
kaggle
fine-tuned
conversational
Instructions to use youssefedweqd/working with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use youssefedweqd/working with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="youssefedweqd/working") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("youssefedweqd/working", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use youssefedweqd/working with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "youssefedweqd/working" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "youssefedweqd/working", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/youssefedweqd/working
- SGLang
How to use youssefedweqd/working 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 "youssefedweqd/working" \ --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": "youssefedweqd/working", "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 "youssefedweqd/working" \ --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": "youssefedweqd/working", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use youssefedweqd/working with Docker Model Runner:
docker model run hf.co/youssefedweqd/working
| # Copyright 2025 the LlamaFactory team. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
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| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
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| CSS = r""" | |
| .duplicate-button { | |
| margin: auto !important; | |
| color: white !important; | |
| background: black !important; | |
| border-radius: 100vh !important; | |
| } | |
| .thinking-summary { | |
| padding: 8px !important; | |
| } | |
| .thinking-summary span { | |
| border-radius: 4px !important; | |
| padding: 4px !important; | |
| cursor: pointer !important; | |
| font-size: 14px !important; | |
| background: rgb(245, 245, 245) !important; | |
| } | |
| .dark .thinking-summary span { | |
| background: rgb(73, 73, 73) !important; | |
| } | |
| .thinking-container { | |
| border-left: 2px solid #a6a6a6 !important; | |
| padding-left: 10px !important; | |
| margin: 4px 0 !important; | |
| } | |
| .thinking-container p { | |
| color: #a6a6a6 !important; | |
| } | |
| .modal-box { | |
| position: fixed !important; | |
| top: 50%; | |
| left: 50%; | |
| transform: translate(-50%, -50%); /* center horizontally */ | |
| max-width: 1000px; | |
| max-height: 750px; | |
| overflow-y: auto; | |
| background-color: var(--input-background-fill); | |
| flex-wrap: nowrap !important; | |
| border: 2px solid black !important; | |
| z-index: 1000; | |
| padding: 10px; | |
| } | |
| .dark .modal-box { | |
| border: 2px solid white !important; | |
| } | |
| """ | |