Text Generation
Transformers
Safetensors
PyTorch
phi
custom_code
text-generation-inference
8-bit precision
Instructions to use IvanD2002/finetuned-phi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IvanD2002/finetuned-phi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="IvanD2002/finetuned-phi", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("IvanD2002/finetuned-phi", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("IvanD2002/finetuned-phi", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use IvanD2002/finetuned-phi with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "IvanD2002/finetuned-phi" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "IvanD2002/finetuned-phi", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/IvanD2002/finetuned-phi
- SGLang
How to use IvanD2002/finetuned-phi 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 "IvanD2002/finetuned-phi" \ --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": "IvanD2002/finetuned-phi", "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 "IvanD2002/finetuned-phi" \ --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": "IvanD2002/finetuned-phi", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use IvanD2002/finetuned-phi with Docker Model Runner:
docker model run hf.co/IvanD2002/finetuned-phi
Upload 8 files
Browse files- added_tokens.json +40 -0
- config.json +34 -0
- generation_config.json +4 -0
- merges.txt +0 -0
- special_tokens_map.json +5 -0
- tokenizer.json +0 -0
- tokenizer_config.json +9 -0
- vocab.json +0 -0
added_tokens.json
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}
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config.json
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{
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"_name_or_path": "microsoft/phi-1_5",
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"architectures": [
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"PhiForCausalLM"
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],
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"auto_map": {
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"AutoConfig": "configuration_phi.PhiConfig",
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"AutoModelForCausalLM": "modeling_phi.PhiForCausalLM"
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},
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"attention_dropout": 0.0,
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"bos_token_id": null,
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"embd_pdrop": 0.0,
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"eos_token_id": null,
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"hidden_act": "gelu_new",
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"hidden_size": 2048,
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"initializer_range": 0.02,
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"intermediate_size": 8192,
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 2048,
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"model_type": "phi",
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"num_attention_heads": 32,
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"num_hidden_layers": 24,
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"num_key_value_heads": null,
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"partial_rotary_factor": 0.5,
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"qk_layernorm": false,
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"resid_pdrop": 0.0,
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"rope_scaling": null,
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"rope_theta": 10000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "float16",
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"transformers_version": "4.37.0",
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"use_cache": true,
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"vocab_size": 51200
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}
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generation_config.json
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"_from_model_config": true,
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"transformers_version": "4.37.0.dev0"
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}
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merges.txt
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special_tokens_map.json
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"bos_token": "<|endoftext|>",
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"eos_token": "<|endoftext|>",
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"unk_token": "<|endoftext|>"
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}
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tokenizer.json
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tokenizer_config.json
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{
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"add_prefix_space": false,
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"bos_token": "<|endoftext|>",
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"clean_up_tokenization_spaces": true,
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"eos_token": "<|endoftext|>",
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"model_max_length": 2048,
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"tokenizer_class": "CodeGenTokenizer",
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"unk_token": "<|endoftext|>"
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}
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vocab.json
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