Instructions to use vext-ma/silma-2b-darija-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use vext-ma/silma-2b-darija-lora with PEFT:

from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("silma-ai/SILMA-Kashif-2B-Instruct-v1.0")
model = PeftModel.from_pretrained(base_model, "vext-ma/silma-2b-darija-lora")

Transformers

How to use vext-ma/silma-2b-darija-lora with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="vext-ma/silma-2b-darija-lora")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("vext-ma/silma-2b-darija-lora", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use vext-ma/silma-2b-darija-lora with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "vext-ma/silma-2b-darija-lora"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "vext-ma/silma-2b-darija-lora",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/vext-ma/silma-2b-darija-lora

SGLang

How to use vext-ma/silma-2b-darija-lora 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 "vext-ma/silma-2b-darija-lora" \
    --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": "vext-ma/silma-2b-darija-lora",
		"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 "vext-ma/silma-2b-darija-lora" \
        --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": "vext-ma/silma-2b-darija-lora",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use vext-ma/silma-2b-darija-lora with Docker Model Runner:
```
docker model run hf.co/vext-ma/silma-2b-darija-lora
```

silma-2b-darija-lora / tokenizer_config.json

abdnaouri

🇲🇦 Upload SILMA-2B-Darija LoRA adapter, tokenizer, and model card

c4f7368 verified about 2 months ago

Raw History Blame Contribute Delete

578 Bytes

{
  "backend": "tokenizers",
  "bos_token": "<bos>",
  "clean_up_tokenization_spaces": false,
  "eos_token": "<eos>",
  "extra_special_tokens": [
    "<start_of_turn>",
    "<end_of_turn>"
  ],
  "is_local": false,
  "local_files_only": false,
  "mask_token": "<mask>",
  "model_max_length": 1000000000000000019884624838656,
  "pad_token": "<pad>",
  "padding_side": "right",
  "sp_model_kwargs": {},
  "spaces_between_special_tokens": false,
  "split_special_tokens": false,
  "tokenizer_class": "GemmaTokenizer",
  "unk_token": "<unk>",
  "use_default_system_prompt": false
}

	{
	"backend": "tokenizers",
	"bos_token": "<bos>",
	"clean_up_tokenization_spaces": false,
	"eos_token": "<eos>",
	"extra_special_tokens": [
	"<start_of_turn>",
	"<end_of_turn>"
	],
	"is_local": false,
	"local_files_only": false,
	"mask_token": "<mask>",
	"model_max_length": 1000000000000000019884624838656,
	"pad_token": "<pad>",
	"padding_side": "right",
	"sp_model_kwargs": {},
	"spaces_between_special_tokens": false,
	"split_special_tokens": false,
	"tokenizer_class": "GemmaTokenizer",
	"unk_token": "<unk>",
	"use_default_system_prompt": false
	}