Instructions to use b3x0m/xomdich-mobile with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use b3x0m/xomdich-mobile with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="b3x0m/xomdich-mobile") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("b3x0m/xomdich-mobile", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use b3x0m/xomdich-mobile with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "b3x0m/xomdich-mobile" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "b3x0m/xomdich-mobile", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/b3x0m/xomdich-mobile
- SGLang
How to use b3x0m/xomdich-mobile 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 "b3x0m/xomdich-mobile" \ --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": "b3x0m/xomdich-mobile", "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 "b3x0m/xomdich-mobile" \ --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": "b3x0m/xomdich-mobile", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use b3x0m/xomdich-mobile with Docker Model Runner:
docker model run hf.co/b3x0m/xomdich-mobile
Update tokenizer_config.json
Browse files- tokenizer_config.json +1 -1
tokenizer_config.json
CHANGED
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@@ -36,7 +36,7 @@
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"legacy": true,
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"max_model_input_sizes": 2048,
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"model_max_length": 1000000000000000019884624838656,
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"tokenizer_class": "
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"unk_token": "<unk>",
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"unk_token_id": 0,
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"use_default_system_prompt": false
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"legacy": true,
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"max_model_input_sizes": 2048,
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"model_max_length": 1000000000000000019884624838656,
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+
"tokenizer_class": "PreTrainedTokenizerFast",
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"unk_token": "<unk>",
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"unk_token_id": 0,
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"use_default_system_prompt": false
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