Text Generation
Transformers
Safetensors
qwen3
solo
fine-tuned
lora
unsloth
conversational
text-generation-inference
Instructions to use zeeshaan-ai/GetSoloTech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zeeshaan-ai/GetSoloTech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="zeeshaan-ai/GetSoloTech") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("zeeshaan-ai/GetSoloTech") model = AutoModelForCausalLM.from_pretrained("zeeshaan-ai/GetSoloTech", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=256) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use zeeshaan-ai/GetSoloTech with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "zeeshaan-ai/GetSoloTech" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "zeeshaan-ai/GetSoloTech", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/zeeshaan-ai/GetSoloTech
- SGLang
How to use zeeshaan-ai/GetSoloTech 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 "zeeshaan-ai/GetSoloTech" \ --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": "zeeshaan-ai/GetSoloTech", "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 "zeeshaan-ai/GetSoloTech" \ --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": "zeeshaan-ai/GetSoloTech", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Unsloth Desktop
- Docker Model Runner
How to use zeeshaan-ai/GetSoloTech with Docker Model Runner:
docker model run hf.co/zeeshaan-ai/GetSoloTech
Download policy_preprocessor_step_2_normalizer_processor.safetensors from zeeshaan-ai/GetSoloTech: direct link, hf CLI and curl.
- Browser
- Download file 3.76 kB
-
https://huggingface.co/zeeshaan-ai/GetSoloTech/resolve/main/policy_preprocessor_step_2_normalizer_processor.safetensors
- Command line
-
hf download hf://zeeshaan-ai/GetSoloTech/policy_preprocessor_step_2_normalizer_processor.safetensors
-
curl -L -o policy_preprocessor_step_2_normalizer_processor.safetensors https://huggingface.co/zeeshaan-ai/GetSoloTech/resolve/main/policy_preprocessor_step_2_normalizer_processor.safetensors
3.76 kB
- Xet hash:
- c91cb97f02e1c228ef0d90160dcf61a6dd446e10b9ac053468c2525c64cace04
- Size of remote file:
- 3.76 kB
- SHA256:
- 0d3a29f5c48d4a834715c06fbcb2082ef14fde4a98f373a7a3e05d42375580ed
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