Instructions to use parasora/tinycodellama-jp-0.3b-15k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use parasora/tinycodellama-jp-0.3b-15k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="parasora/tinycodellama-jp-0.3b-15k")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("parasora/tinycodellama-jp-0.3b-15k") model = AutoModelForCausalLM.from_pretrained("parasora/tinycodellama-jp-0.3b-15k") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use parasora/tinycodellama-jp-0.3b-15k with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "parasora/tinycodellama-jp-0.3b-15k" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "parasora/tinycodellama-jp-0.3b-15k", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/parasora/tinycodellama-jp-0.3b-15k
- SGLang
How to use parasora/tinycodellama-jp-0.3b-15k 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 "parasora/tinycodellama-jp-0.3b-15k" \ --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": "parasora/tinycodellama-jp-0.3b-15k", "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 "parasora/tinycodellama-jp-0.3b-15k" \ --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": "parasora/tinycodellama-jp-0.3b-15k", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use parasora/tinycodellama-jp-0.3b-15k with Docker Model Runner:
docker model run hf.co/parasora/tinycodellama-jp-0.3b-15k
File size: 1,935 Bytes
70da551 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 | {
"added_tokens_decoder": {
"0": {
"content": "<unk|LLM-jp>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"1": {
"content": "<s|LLM-jp>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"2": {
"content": "</s|LLM-jp>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"3": {
"content": "<mask|LLM-jp>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"4": {
"content": "<pad|LLM-jp>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"5": {
"content": "<CLS|LLM-jp>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"6": {
"content": "<SEP|LLM-jp>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"7": {
"content": "<EOD|LLM-jp>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
}
},
"additional_special_tokens": [
"</s|LLM-jp>"
],
"bos_token": "<s|LLM-jp>",
"clean_up_tokenization_spaces": false,
"cls_token": "<CLS|LLM-jp>",
"eod_token": "<EOD|LLM-jp>",
"eos_token": "<EOD|LLM-jp>",
"extra_ids": 0,
"legacy": false,
"mask_token": "<mask|LLM-jp>",
"model_max_length": 1000000000000000019884624838656,
"pad_token": "<pad|LLM-jp>",
"sep_token": "<SEP|LLM-jp>",
"sp_model_kwargs": {},
"tokenizer_class": "PreTrainedTokenizerFast",
"unk_token": "<unk|LLM-jp>"
}
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