Text Generation
PEFT
Safetensors
Transformers
diegetic
epistemic-reasoning
belief-state
theory-of-mind
lora
sft
trl
conversational
Instructions to use howellx/diegetic-1.5b-sft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use howellx/diegetic-1.5b-sft with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-1.5B") model = PeftModel.from_pretrained(base_model, "howellx/diegetic-1.5b-sft") - Transformers
How to use howellx/diegetic-1.5b-sft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="howellx/diegetic-1.5b-sft") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("howellx/diegetic-1.5b-sft", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use howellx/diegetic-1.5b-sft with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "howellx/diegetic-1.5b-sft" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "howellx/diegetic-1.5b-sft", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/howellx/diegetic-1.5b-sft
- SGLang
How to use howellx/diegetic-1.5b-sft 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 "howellx/diegetic-1.5b-sft" \ --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": "howellx/diegetic-1.5b-sft", "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 "howellx/diegetic-1.5b-sft" \ --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": "howellx/diegetic-1.5b-sft", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use howellx/diegetic-1.5b-sft with Docker Model Runner:
docker model run hf.co/howellx/diegetic-1.5b-sft
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| "add_bos_token": false, | |
| "add_prefix_space": false, | |
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| }, | |
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| "151665": { | |
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| "lstrip": false, | |
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| "content": "<EPISTEMIC>", | |
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| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151676": { | |
| "content": "<REFUSE_DIEGETIC>", | |
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| "normalized": false, | |
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| "single_word": false, | |
| "special": true | |
| } | |
| }, | |
| "additional_special_tokens": [ | |
| "<OBS>", | |
| "</OBS>", | |
| "<BELIEF>", | |
| "</BELIEF>", | |
| "<MEM>", | |
| "</MEM>", | |
| "<TASK>", | |
| "</TASK>", | |
| "<OUTPUT_JSON>", | |
| "</OUTPUT_JSON>", | |
| "<EPISTEMIC>", | |
| "<REFUSE_DIEGETIC>" | |
| ], | |
| "bos_token": null, | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|endoftext|>", | |
| "errors": "replace", | |
| "extra_special_tokens": {}, | |
| "model_max_length": 131072, | |
| "pad_token": "<|endoftext|>", | |
| "split_special_tokens": false, | |
| "tokenizer_class": "Qwen2Tokenizer", | |
| "unk_token": null | |
| } | |