Text Generation
Transformers
Safetensors
PyTorch
English
fineweb_decoder
causal-lm
custom-code
educational
custom_code
Instructions to use PeterRabbit/fineweb-100m-sft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PeterRabbit/fineweb-100m-sft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="PeterRabbit/fineweb-100m-sft", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("PeterRabbit/fineweb-100m-sft", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use PeterRabbit/fineweb-100m-sft with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "PeterRabbit/fineweb-100m-sft" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "PeterRabbit/fineweb-100m-sft", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/PeterRabbit/fineweb-100m-sft
- SGLang
How to use PeterRabbit/fineweb-100m-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 "PeterRabbit/fineweb-100m-sft" \ --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": "PeterRabbit/fineweb-100m-sft", "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 "PeterRabbit/fineweb-100m-sft" \ --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": "PeterRabbit/fineweb-100m-sft", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use PeterRabbit/fineweb-100m-sft with Docker Model Runner:
docker model run hf.co/PeterRabbit/fineweb-100m-sft
| { | |
| "architectures": [ | |
| "FineWebForCausalLM" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_fineweb.FineWebConfig", | |
| "AutoModelForCausalLM": "modeling_fineweb.FineWebForCausalLM" | |
| }, | |
| "model_type": "fineweb_decoder", | |
| "vocab_size": 16384, | |
| "n_layers": 12, | |
| "d_model": 768, | |
| "n_heads": 12, | |
| "mlp_hidden": 2048, | |
| "context_length": 1024, | |
| "max_position_embeddings": 1024, | |
| "rms_norm_eps": 1e-06, | |
| "bos_token_id": 0, | |
| "eos_token_id": 1, | |
| "pad_token_id": 1, | |
| "unk_token_id": 2, | |
| "tie_word_embeddings": true, | |
| "use_cache": false, | |
| "torch_dtype": "float32" | |
| } | |