Text Generation
Transformers
Safetensors
phi
axolotl
Generated from Trainer
conversational
text-generation-inference
Instructions to use SystemAdmin123/tiny-random-PhiForCausalLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SystemAdmin123/tiny-random-PhiForCausalLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="SystemAdmin123/tiny-random-PhiForCausalLM") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("SystemAdmin123/tiny-random-PhiForCausalLM") model = AutoModelForCausalLM.from_pretrained("SystemAdmin123/tiny-random-PhiForCausalLM", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=256) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use SystemAdmin123/tiny-random-PhiForCausalLM with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SystemAdmin123/tiny-random-PhiForCausalLM" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SystemAdmin123/tiny-random-PhiForCausalLM", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/SystemAdmin123/tiny-random-PhiForCausalLM
- SGLang
How to use SystemAdmin123/tiny-random-PhiForCausalLM 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 "SystemAdmin123/tiny-random-PhiForCausalLM" \ --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": "SystemAdmin123/tiny-random-PhiForCausalLM", "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 "SystemAdmin123/tiny-random-PhiForCausalLM" \ --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": "SystemAdmin123/tiny-random-PhiForCausalLM", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use SystemAdmin123/tiny-random-PhiForCausalLM with Docker Model Runner:
docker model run hf.co/SystemAdmin123/tiny-random-PhiForCausalLM
Download axolotl_config.yaml from SystemAdmin123/tiny-random-PhiForCausalLM: direct link, hf CLI and curl.
- Browser
- Download file 1.45 kB
-
https://huggingface.co/SystemAdmin123/tiny-random-PhiForCausalLM/resolve/main/axolotl_config.yaml
- Command line
-
hf download hf://SystemAdmin123/tiny-random-PhiForCausalLM/axolotl_config.yaml
-
curl -L -o axolotl_config.yaml https://huggingface.co/SystemAdmin123/tiny-random-PhiForCausalLM/resolve/main/axolotl_config.yaml
1.45 kB
| base_model: echarlaix/tiny-random-PhiForCausalLM | |
| batch_size: 128 | |
| bf16: true | |
| chat_template: tokenizer_default_fallback_alpaca | |
| datasets: | |
| - format: custom | |
| path: argilla/databricks-dolly-15k-curated-en | |
| type: | |
| field_input: original-instruction | |
| field_instruction: original-instruction | |
| field_output: original-response | |
| format: '{instruction} {input}' | |
| no_input_format: '{instruction}' | |
| system_format: '{system}' | |
| system_prompt: '' | |
| device_map: auto | |
| eval_sample_packing: false | |
| eval_steps: 200 | |
| flash_attention: true | |
| gradient_checkpointing: true | |
| group_by_length: true | |
| hub_model_id: SystemAdmin123/tiny-random-PhiForCausalLM | |
| hub_strategy: checkpoint | |
| learning_rate: 0.0002 | |
| logging_steps: 10 | |
| lr_scheduler: cosine | |
| max_steps: 10000 | |
| micro_batch_size: 32 | |
| model_type: AutoModelForCausalLM | |
| num_epochs: 100 | |
| optimizer: adamw_bnb_8bit | |
| output_dir: /root/.sn56/axolotl/tmp/tiny-random-PhiForCausalLM | |
| pad_to_sequence_len: true | |
| resize_token_embeddings_to_32x: false | |
| sample_packing: true | |
| save_steps: 200 | |
| save_total_limit: 1 | |
| sequence_len: 2048 | |
| special_tokens: | |
| pad_token: <|endoftext|> | |
| tokenizer_type: GPTNeoXTokenizerFast | |
| torch_dtype: bf16 | |
| training_args_kwargs: | |
| hub_private_repo: true | |
| trust_remote_code: true | |
| val_set_size: 0.1 | |
| wandb_entity: '' | |
| wandb_mode: online | |
| wandb_name: echarlaix/tiny-random-PhiForCausalLM-argilla/databricks-dolly-15k-curated-en | |
| wandb_project: Gradients-On-Demand | |
| wandb_run: your_name | |
| wandb_runid: default | |
| warmup_ratio: 0.05 | |