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
Upload DataProcessorPipeline
Browse files
policy_preprocessor.json
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{
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"name": "policy_preprocessor",
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"steps": [
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{
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"registry_name": "rename_observations_processor",
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"config": {
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"rename_map": {}
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}
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},
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{
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"registry_name": "to_batch_processor",
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"config": {}
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},
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{
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"registry_name": "device_processor",
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"config": {
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"device": "cuda",
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"float_dtype": null
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}
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},
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{
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"registry_name": "normalizer_processor",
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"config": {
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"eps": 1e-08,
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"features": {
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"observation.state": {
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"type": "STATE",
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"shape": [
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6
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]
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},
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"observation.images.side": {
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"type": "VISUAL",
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"shape": [
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3,
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1080,
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1920
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]
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},
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"observation.images.front": {
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"type": "VISUAL",
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"shape": [
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3,
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480,
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640
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]
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},
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"action": {
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"type": "ACTION",
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"shape": [
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6
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]
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}
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},
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"norm_map": {
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"VISUAL": "MEAN_STD",
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"STATE": "MEAN_STD",
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"ACTION": "MEAN_STD"
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}
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},
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"state_file": "policy_preprocessor_step_3_normalizer_processor.safetensors"
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}
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]
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}
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policy_preprocessor_step_3_normalizer_processor.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:0d3a29f5c48d4a834715c06fbcb2082ef14fde4a98f373a7a3e05d42375580ed
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size 3756
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