Text Generation
Transformers
Safetensors
llama
trl
sft
Generated from Trainer
conversational
text-generation-inference
Instructions to use yzhuang/phi-1_5_fictional with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yzhuang/phi-1_5_fictional with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="yzhuang/phi-1_5_fictional") 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("yzhuang/phi-1_5_fictional") model = AutoModelForCausalLM.from_pretrained("yzhuang/phi-1_5_fictional", 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 yzhuang/phi-1_5_fictional with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "yzhuang/phi-1_5_fictional" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "yzhuang/phi-1_5_fictional", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/yzhuang/phi-1_5_fictional
- SGLang
How to use yzhuang/phi-1_5_fictional 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 "yzhuang/phi-1_5_fictional" \ --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": "yzhuang/phi-1_5_fictional", "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 "yzhuang/phi-1_5_fictional" \ --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": "yzhuang/phi-1_5_fictional", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use yzhuang/phi-1_5_fictional with Docker Model Runner:
docker model run hf.co/yzhuang/phi-1_5_fictional
Commit History
-
End of training
Verified signature8144e3d -
Training in progress, step 40000
Verified signaturee96ea6c -
Training in progress, step 37500
Verified signature2c40d76 -
Training in progress, step 35000
Verified signature251b72c -
Training in progress, step 32500
Verified signature5fc1c64 -
Training in progress, step 30000
Verified signaturef4e9a1f -
Training in progress, step 27500
Verified signature9c2c5df -
Training in progress, step 25000
Verified signature005d91d -
Training in progress, step 22500
Verified signature7d4369f -
Training in progress, step 20000
Verified signature7b2b656 -
Training in progress, step 17500
Verified signature3fe2a71 -
Training in progress, step 15000
Verified signature06c4590 -
Training in progress, step 12500
Verified signature96d9b6a -
Training in progress, step 10000
Verified signaturee7d90a7 -
Training in progress, step 7500
Verified signaturefcebad0 -
Training in progress, step 5000
Verified signaturee26a2e9 -
Training in progress, step 2500
Verified signature1bf6d7c
-
End of training
Verified signature3fe2a80 -
End of training
Verified signaturec924255 -
End of training
Verified signature78f04d1 -
End of training
Verified signatureeaff4bb -
End of training
Verified signaturef5462cf -
End of training
Verified signature341d126 -
Training in progress, step 5000
Verified signature41c3014 -
Training in progress, step 2500
Verified signature512a3eb -
End of training
Verified signature91b618a -
Training in progress, step 5000
Verified signature5d34958 -
Training in progress, step 2500
Verified signature49700a5
-
End of training
Verified signature419f00e -
End of training
Verified signature0d921b2 -
Training in progress, step 7500
Verified signature5e6d807 -
Training in progress, step 5000
Verified signatureea56284 -
Training in progress, step 2500
Verified signaturec9ea6ff -
End of training
Verified signature39eca97 -
End of training
Verified signature50a10c1 -
Training in progress, step 7500
Verified signature1f4a7b4 -
Training in progress, step 5000
Verified signature6b56147 -
Training in progress, step 2500
Verified signatured8f956f -
End of training
Verified signaturecb13164 -
End of training
Verified signature1135ae7 -
Training in progress, step 5000
Verified signaturee1e97bd -
Training in progress, step 2500
Verified signatureb7da6e0 -
End of training
Verified signature80913fe -
Training in progress, step 5000
Verified signature12ed82c -
Training in progress, step 2500
Verified signature12c886c
-
End of training
Verified signature38ffb4f -
Training in progress, step 35000
Verified signature2fc406f -
Training in progress, step 32500
Verified signature62dba29 -
Training in progress, step 30000
Verified signaturee3f6fa5 -
Training in progress, step 27500
Verified signature4bc314e