Instructions to use Pamzyy/testcode with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Pamzyy/testcode with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Pamzyy/testcode")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Pamzyy/testcode") model = AutoModelForCausalLM.from_pretrained("Pamzyy/testcode") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Pamzyy/testcode with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Pamzyy/testcode" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Pamzyy/testcode", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Pamzyy/testcode
- SGLang
How to use Pamzyy/testcode 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 "Pamzyy/testcode" \ --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": "Pamzyy/testcode", "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 "Pamzyy/testcode" \ --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": "Pamzyy/testcode", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Pamzyy/testcode with Docker Model Runner:
docker model run hf.co/Pamzyy/testcode
Training in progress, step 5
Browse files- config.json +2 -2
- model-00001-of-00007.safetensors +1 -1
- model-00007-of-00007.safetensors +1 -1
- tokenizer_config.json +1 -8
- training_args.bin +2 -2
config.json
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{
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"_name_or_path": "
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"architectures": [
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"LlamaForCausalLM"
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"tie_word_embeddings": false,
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"torch_dtype": "float32",
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"transformers_version": "4.47.1",
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"use_cache":
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"vocab_size": 138626
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{
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"_name_or_path": "meta-llama/Meta-Llama-3.1-8B",
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"architectures": [
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"LlamaForCausalLM"
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],
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"tie_word_embeddings": false,
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"torch_dtype": "float32",
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"transformers_version": "4.47.1",
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"use_cache": true,
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"vocab_size": 138626
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}
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model-00001-of-00007.safetensors
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model-00007-of-00007.safetensors
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tokenizer_config.json
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"clean_up_tokenization_spaces": true,
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"eos_token": "<|end_of_text|>",
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"extra_special_tokens": {},
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"max_length": 512,
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"model_input_names": [
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"input_ids",
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"attention_mask"
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],
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"model_max_length": 131072,
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"pad_to_multiple_of": null,
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"pad_token": "<|end_of_text|>",
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"
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"padding_side": "right",
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"stride": 0,
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"tokenizer_class": "PreTrainedTokenizerFast",
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"truncation_strategy": "longest_first"
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"clean_up_tokenization_spaces": true,
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"eos_token": "<|end_of_text|>",
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"extra_special_tokens": {},
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"model_input_names": [
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"attention_mask"
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"tokenizer_class": "PreTrainedTokenizerFast"
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training_args.bin
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size 5304
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