Instructions to use PYTHAI/mindXtrain39 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use PYTHAI/mindXtrain39 with Transformers:

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

pipe = pipeline("text-generation", model="PYTHAI/mindXtrain39")
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("PYTHAI/mindXtrain39")
model = AutoModelForCausalLM.from_pretrained("PYTHAI/mindXtrain39", 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 PYTHAI/mindXtrain39 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "PYTHAI/mindXtrain39"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "PYTHAI/mindXtrain39",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/PYTHAI/mindXtrain39

SGLang

How to use PYTHAI/mindXtrain39 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 "PYTHAI/mindXtrain39" \
    --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": "PYTHAI/mindXtrain39",
		"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 "PYTHAI/mindXtrain39" \
        --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": "PYTHAI/mindXtrain39",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use PYTHAI/mindXtrain39 with Docker Model Runner:
```
docker model run hf.co/PYTHAI/mindXtrain39
```

mindXtrain39

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{
 "model": "PYTHAI/mindXtrain39",
 "generation": 39,
 "kind": "mindx.generation",
 "base": "HuggingFaceTB/SmolLM2-135M",
 "params": "135M",
 "arch": "llama",
 "adapter": {
  "kind": "lora",
  "r": 16,
  "alpha": 32,
  "targets": [
   "q_proj",
   "k_proj",
   "v_proj",
   "o_proj"
  ],
  "merged": true
 },
 "chat": {
  "template": "chatml",
  "stop": [
   "<|im_end|>"
  ],
  "decoding_for_comparable_scores": {
   "do_sample": false,
   "repetition_penalty": 1.3,
   "no_repeat_ngram_size": 3,
   "max_new_tokens": 96
  }
 },
 "gate": {
  "imprint_delta_recall": 0.1002,
  "imprinted": true,
  "stage": "accepted",
  "promoted_at_the_time": false
 },
 "coach": {
  "probe_battery": "mindXtrain default_inquiries + corpus rows the generation trained on",
  "scorers": "mindx/godel/mindxtrain/scorers.py (identity · task · coherence)",
  "influence": "always measured against the untouched base answering the same probe",
  "measured_on_this_generation": {
   "runs": 3,
   "recall_delta": 0.0023,
   "coherence_delta": -0.2014,
   "identity_delta": 0.0
  }
 },
 "inference": {
  "local_ollama": "mindXtrain39",
  "space": "https://gregory-l-mindxhfgradio.hf.space",
  "mcp": "the Space is an MCP server; `probe` is a tool",
  "node": "https://mindx.pythai.net"
 },
 "policy": {
  "educational": "educational.policy.json",
  "drill": "bootcamp.impression.json",
  "feedback": "impression.bootcamp.json"
 },
 "provenance": {
  "thot": "THOT.json",
  "inft_facets": "inft/",
  "lineage_dataset": "PYTHAI/mindXascension",
  "ascent_log": "data/logs/ascend_log.jsonl",
  "registry": "https://mindx.pythai.net/insight/hf/registry"
 },
 "honesty": "135M with a recall imprint. Not a general assistant; the coach's verdict on this lineage is NOT interaction-ready (identity 16%)."
}