Instructions to use Skskskd/teste-modelo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Skskskd/teste-modelo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Skskskd/teste-modelo")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Skskskd/teste-modelo") model = AutoModelForCausalLM.from_pretrained("Skskskd/teste-modelo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Skskskd/teste-modelo with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Skskskd/teste-modelo" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Skskskd/teste-modelo", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Skskskd/teste-modelo
- SGLang
How to use Skskskd/teste-modelo 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 "Skskskd/teste-modelo" \ --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": "Skskskd/teste-modelo", "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 "Skskskd/teste-modelo" \ --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": "Skskskd/teste-modelo", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Skskskd/teste-modelo with Docker Model Runner:
docker model run hf.co/Skskskd/teste-modelo
Upload tokenizer
Browse files- tokenizer.json +9 -0
- tokenizer_config.json +1 -8
tokenizer.json
CHANGED
|
@@ -11,6 +11,15 @@
|
|
| 11 |
"rstrip": false,
|
| 12 |
"normalized": true,
|
| 13 |
"special": true
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 14 |
}
|
| 15 |
],
|
| 16 |
"normalizer": null,
|
|
|
|
| 11 |
"rstrip": false,
|
| 12 |
"normalized": true,
|
| 13 |
"special": true
|
| 14 |
+
},
|
| 15 |
+
{
|
| 16 |
+
"id": 50257,
|
| 17 |
+
"content": "[PAD]",
|
| 18 |
+
"single_word": false,
|
| 19 |
+
"lstrip": false,
|
| 20 |
+
"rstrip": false,
|
| 21 |
+
"normalized": false,
|
| 22 |
+
"special": true
|
| 23 |
}
|
| 24 |
],
|
| 25 |
"normalizer": null,
|
tokenizer_config.json
CHANGED
|
@@ -6,15 +6,8 @@
|
|
| 6 |
"errors": "replace",
|
| 7 |
"is_local": false,
|
| 8 |
"local_files_only": false,
|
| 9 |
-
"max_length": 128,
|
| 10 |
"model_max_length": 1024,
|
| 11 |
-
"
|
| 12 |
-
"pad_token": "<|endoftext|>",
|
| 13 |
-
"pad_token_type_id": 0,
|
| 14 |
-
"padding_side": "right",
|
| 15 |
-
"stride": 0,
|
| 16 |
"tokenizer_class": "GPT2Tokenizer",
|
| 17 |
-
"truncation_side": "right",
|
| 18 |
-
"truncation_strategy": "longest_first",
|
| 19 |
"unk_token": "<|endoftext|>"
|
| 20 |
}
|
|
|
|
| 6 |
"errors": "replace",
|
| 7 |
"is_local": false,
|
| 8 |
"local_files_only": false,
|
|
|
|
| 9 |
"model_max_length": 1024,
|
| 10 |
+
"pad_token": "[PAD]",
|
|
|
|
|
|
|
|
|
|
|
|
|
| 11 |
"tokenizer_class": "GPT2Tokenizer",
|
|
|
|
|
|
|
| 12 |
"unk_token": "<|endoftext|>"
|
| 13 |
}
|