Text Generation
Transformers
Portuguese
English
nanochat
nanochatpt
portuguese
pt-pt
instruction-tuned
sft
conversational
european-portuguese
Instructions to use inaciose/inacio-sft-d16v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use inaciose/inacio-sft-d16v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="inaciose/inacio-sft-d16v1") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("inaciose/inacio-sft-d16v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use inaciose/inacio-sft-d16v1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "inaciose/inacio-sft-d16v1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "inaciose/inacio-sft-d16v1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/inaciose/inacio-sft-d16v1
- SGLang
How to use inaciose/inacio-sft-d16v1 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 "inaciose/inacio-sft-d16v1" \ --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": "inaciose/inacio-sft-d16v1", "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 "inaciose/inacio-sft-d16v1" \ --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": "inaciose/inacio-sft-d16v1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use inaciose/inacio-sft-d16v1 with Docker Model Runner:
docker model run hf.co/inaciose/inacio-sft-d16v1
| { | |
| "step": 699, | |
| "val_bpb": 0.15301302843251394, | |
| "model_config": { | |
| "sequence_len": 2048, | |
| "vocab_size": 65536, | |
| "n_layer": 16, | |
| "n_head": 8, | |
| "n_kv_head": 8, | |
| "n_embd": 1024, | |
| "window_pattern": "SSSL" | |
| }, | |
| "user_config": { | |
| "run": "nanochatpt-d16-full", | |
| "device_type": "", | |
| "model_tag": null, | |
| "model_step": null, | |
| "load_optimizer": 1, | |
| "num_iterations": -1, | |
| "max_seq_len": null, | |
| "device_batch_size": 4, | |
| "total_batch_size": null, | |
| "embedding_lr": null, | |
| "unembedding_lr": null, | |
| "matrix_lr": null, | |
| "init_lr_frac": 0.8, | |
| "warmup_ratio": 0.0, | |
| "warmdown_ratio": 0.5, | |
| "final_lr_frac": 0.0, | |
| "eval_every": 200, | |
| "eval_tokens": 20971520, | |
| "chatcore_every": 200, | |
| "chatcore_max_cat": -1, | |
| "chatcore_max_sample": 24, | |
| "mmlu_epochs": 3, | |
| "gsm8k_epochs": 4 | |
| } | |
| } |