Instructions to use ratishsp/igsm-trace-validity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ratishsp/igsm-trace-validity with Transformers:

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

pipe = pipeline("text-generation", model="ratishsp/igsm-trace-validity")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("ratishsp/igsm-trace-validity", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ratishsp/igsm-trace-validity with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ratishsp/igsm-trace-validity"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ratishsp/igsm-trace-validity",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/ratishsp/igsm-trace-validity

SGLang

How to use ratishsp/igsm-trace-validity 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 "ratishsp/igsm-trace-validity" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ratishsp/igsm-trace-validity",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "ratishsp/igsm-trace-validity" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ratishsp/igsm-trace-validity",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use ratishsp/igsm-trace-validity with Docker Model Runner:
```
docker model run hf.co/ratishsp/igsm-trace-validity
```

igsm-trace-validity / swapped /config.json

ratishsp

Models for Correct Answers, Invalid Traces

8b04096 about 1 month ago

Raw History Blame Contribute Delete

749 Bytes

{
  "architectures": [
    "GPTNeoXForCausalLM"
  ],
  "attention_bias": true,
  "attention_dropout": 0.0,
  "bos_token_id": 0,
  "classifier_dropout": 0.1,
  "dtype": "float32",
  "eos_token_id": 2,
  "hidden_act": "gelu",
  "hidden_dropout": 0.0,
  "hidden_size": 768,
  "initializer_range": 0.02,
  "intermediate_size": 3072,
  "layer_norm_eps": 1e-05,
  "max_position_embeddings": 2048,
  "model_type": "gpt_neox",
  "num_attention_heads": 12,
  "num_hidden_layers": 12,
  "partial_rotary_factor": 1.0,
  "rope_scaling": null,
  "rope_theta": 10000,
  "rotary_emb_base": 10000,
  "rotary_pct": 1.0,
  "tie_word_embeddings": true,
  "transformers_version": "4.57.6",
  "use_cache": true,
  "use_parallel_residual": false,
  "vocab_size": 50257
}

	{
	"architectures": [
	"GPTNeoXForCausalLM"
	],
	"attention_bias": true,
	"attention_dropout": 0.0,
	"bos_token_id": 0,
	"classifier_dropout": 0.1,
	"dtype": "float32",
	"eos_token_id": 2,
	"hidden_act": "gelu",
	"hidden_dropout": 0.0,
	"hidden_size": 768,
	"initializer_range": 0.02,
	"intermediate_size": 3072,
	"layer_norm_eps": 1e-05,
	"max_position_embeddings": 2048,
	"model_type": "gpt_neox",
	"num_attention_heads": 12,
	"num_hidden_layers": 12,
	"partial_rotary_factor": 1.0,
	"rope_scaling": null,
	"rope_theta": 10000,
	"rotary_emb_base": 10000,
	"rotary_pct": 1.0,
	"tie_word_embeddings": true,
	"transformers_version": "4.57.6",
	"use_cache": true,
	"use_parallel_residual": false,
	"vocab_size": 50257
	}