Instructions to use aixk/fastplus-125m-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aixk/fastplus-125m-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="aixk/fastplus-125m-test")# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("aixk/fastplus-125m-test", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use aixk/fastplus-125m-test with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "aixk/fastplus-125m-test" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "aixk/fastplus-125m-test", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/aixk/fastplus-125m-test
- SGLang
How to use aixk/fastplus-125m-test 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 "aixk/fastplus-125m-test" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "aixk/fastplus-125m-test", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "aixk/fastplus-125m-test" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "aixk/fastplus-125m-test", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use aixk/fastplus-125m-test with Docker Model Runner:
docker model run hf.co/aixk/fastplus-125m-test
FastPlus125m Geodesic Backup checkpoint-105 at global step 105
Browse files- checkpoint-105/config.json +19 -0
- checkpoint-105/generation_config.json +6 -0
- checkpoint-105/model.safetensors +3 -0
- checkpoint-105/optimizer.pt +3 -0
- checkpoint-105/rng_state.pth +3 -0
- checkpoint-105/scaler.pt +3 -0
- checkpoint-105/scheduler.pt +3 -0
- checkpoint-105/tokenizer.json +0 -0
- checkpoint-105/tokenizer_config.json +15 -0
- checkpoint-105/trainer_state.json +114 -0
- checkpoint-105/training_args.bin +3 -0
checkpoint-105/config.json
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{
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"architectures": [
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"FastPlus125mForCausalLM"
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],
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"dtype": "float32",
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 2048,
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"kd_alpha": 0.4,
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"kd_temperature": 2.5,
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"max_position_embeddings": 512,
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"model_type": "fastplus_125m",
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"num_attention_heads": 12,
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"num_hidden_layers": 16,
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"tie_word_embeddings": true,
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"transformers_version": "5.12.0",
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"use_cache": false,
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"vocab_size": 1792
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}
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checkpoint-105/generation_config.json
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{
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"_from_model_config": true,
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"output_attentions": false,
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"output_hidden_states": false,
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"transformers_version": "5.12.0"
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}
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checkpoint-105/model.safetensors
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checkpoint-105/optimizer.pt
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checkpoint-105/rng_state.pth
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checkpoint-105/scaler.pt
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version https://git-lfs.github.com/spec/v1
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size 1383
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checkpoint-105/scheduler.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:715d93f94f69cc2a9664de6febc48ab1cd682b7056ab9016d52301f7c2c872b2
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size 7737
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checkpoint-105/tokenizer.json
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checkpoint-105/tokenizer_config.json
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{
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"backend": "tokenizers",
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"bos_token": "<s>",
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"eos_token": "</s>",
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"extra_special_tokens": [
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"<|user|>",
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"<|assistant|>"
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],
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"is_local": false,
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"local_files_only": false,
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"model_max_length": 1000000000000000019884624838656,
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"pad_token": "<pad>",
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"tokenizer_class": "TokenizersBackend",
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"unk_token": "<unk>"
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}
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checkpoint-105/trainer_state.json
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checkpoint-105/training_args.bin
ADDED
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version https://git-lfs.github.com/spec/v1
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| 2 |
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oid sha256:81294502804efcb3a9510bb4aef4a5dfafe7bd4697bb802b14ff6b17f0d6bc98
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size 5201
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