Instructions to use salakash/SamKash-Tolstoy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
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
- 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
Languages spoken
#2
by mirix - opened
Does this thing speak Russian or only English?
It does not speak Russian :D
Напиши рефлективный параграф о совести и судьбе в аристократической семье.
Стаж: 7. Стоимостьparent's job: $100k/yr. Стоимостьchild's job: $150k/yr.
Количествоchild: 3. Всего труда: 30h/wd.
Недоразумение:parent's job income isn't enough to support the family's living expenses.
Рекомендации:1. Find a way to support the family financially.
2. Encourage the child to pursue a career.
3. Provide financial assistance for transportation and housing.
4. Offer a stipend for the child's education.
5. Create a safe and secure environment for the child to live.
6. Offer counseling services.
7. Encourage the child to participate in social activities.
8. Make the parent's job stable.
9. Support the child's job search and integration into the family.
10. Help