Instructions to use salakash/SamKash-Tolstoy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use salakash/SamKash-Tolstoy with PEFT:

from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B")
model = PeftModel.from_pretrained(base_model, "salakash/SamKash-Tolstoy")

Transformers

How to use salakash/SamKash-Tolstoy with Transformers:

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

pipe = pipeline("text-generation", model="salakash/SamKash-Tolstoy")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("salakash/SamKash-Tolstoy", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use salakash/SamKash-Tolstoy with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/salakash/SamKash-Tolstoy

SGLang

How to use salakash/SamKash-Tolstoy 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 "salakash/SamKash-Tolstoy" \
    --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": "salakash/SamKash-Tolstoy",
		"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 "salakash/SamKash-Tolstoy" \
        --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": "salakash/SamKash-Tolstoy",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use salakash/SamKash-Tolstoy with Docker Model Runner:
```
docker model run hf.co/salakash/SamKash-Tolstoy
```

🚩 Report: Spam

by diimdeep - opened Dec 14, 2025

Discussion

diimdeep

Dec 14, 2025

Not usable, upvoted by apparent bot network of accounts.

salakash

Owner Dec 14, 2025

Please see the model card for intended use cases, limitations, and 'how to use it'. Please let me know where you are stuck, or looking for the improvement. Also, this isn’t theoretical. The model is already in active use today by the Virtual Library, as an add-on and by academics, which is a strong signal that it’s usable when applied within the documented scope and constraints.

salakash locked this discussion Dec 16, 2025

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