Instructions to use zeeshaan-ai/GetSoloTech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("zeeshaan-ai/GetSoloTech")
model = AutoModelForCausalLM.from_pretrained("zeeshaan-ai/GetSoloTech")
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=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps

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 Studio new

How to use zeeshaan-ai/GetSoloTech with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for zeeshaan-ai/GetSoloTech to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for zeeshaan-ai/GetSoloTech to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for zeeshaan-ai/GetSoloTech to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="zeeshaan-ai/GetSoloTech",
    max_seq_length=2048,
)

Docker Model Runner
How to use zeeshaan-ai/GetSoloTech with Docker Model Runner:
```
docker model run hf.co/zeeshaan-ai/GetSoloTech
```

zeeshaan-ai commited on Mar 6

Commit

5ff352a

verified ·

1 Parent(s): fdef9b5

Upload DataProcessorPipeline

Browse files

Files changed (2) hide show

policy_preprocessor.json +25 -25
policy_preprocessor_step_2_normalizer_processor.safetensors +3 -0

policy_preprocessor.json CHANGED Viewed

@@ -11,28 +11,6 @@
       "registry_name": "to_batch_processor",
       "config": {}
     },
-    {
-      "registry_name": "smolvla_new_line_processor",
-      "config": {}
-    },
-    {
-      "registry_name": "tokenizer_processor",
-      "config": {
-        "max_length": 48,
-        "task_key": "task",
-        "padding_side": "right",
-        "padding": "max_length",
-        "truncation": true,
-        "tokenizer_name": "HuggingFaceTB/SmolVLM2-500M-Video-Instruct"
-      }
-    },
-    {
-      "registry_name": "device_processor",
-      "config": {
-        "device": "cuda",
-        "float_dtype": null
-      }
-    },
     {
       "registry_name": "normalizer_processor",
       "config": {
@@ -68,12 +46,34 @@
           }
         },
         "norm_map": {
-          "VISUAL": "IDENTITY",
           "STATE": "MEAN_STD",
-          "ACTION": "MEAN_STD"
         }
       },
-      "state_file": "policy_preprocessor_step_5_normalizer_processor.safetensors"
     }
   ]
 }

       "registry_name": "to_batch_processor",
       "config": {}
     },
     {
       "registry_name": "normalizer_processor",
       "config": {
           }
         },
         "norm_map": {
+          "ACTION": "MEAN_STD",
           "STATE": "MEAN_STD",
+          "VISUAL": "IDENTITY"
         }
       },
+      "state_file": "policy_preprocessor_step_2_normalizer_processor.safetensors"
+    },
+    {
+      "registry_name": "pi05_prepare_state_tokenizer_processor_step",
+      "config": {}
+    },
+    {
+      "registry_name": "tokenizer_processor",
+      "config": {
+        "max_length": 200,
+        "task_key": "task",
+        "padding_side": "right",
+        "padding": "max_length",
+        "truncation": true,
+        "tokenizer_name": "google/paligemma-3b-pt-224"
+      }
+    },
+    {
+      "registry_name": "device_processor",
+      "config": {
+        "device": "cuda",
+        "float_dtype": null
+      }
     }
   ]
 }

policy_preprocessor_step_2_normalizer_processor.safetensors ADDED Viewed

	@@ -0,0 +1,3 @@

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+size 3756