Text Generation
Transformers
Safetensors
English
testgeniy
causal-lm
reasoning
mathematics
logic
long-context
4k-context
small-language-model
Instructions to use Asilarkness/testgeniy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Asilarkness/testgeniy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Asilarkness/testgeniy")# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Asilarkness/testgeniy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Asilarkness/testgeniy with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Asilarkness/testgeniy" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Asilarkness/testgeniy", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Asilarkness/testgeniy
- SGLang
How to use Asilarkness/testgeniy 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 "Asilarkness/testgeniy" \ --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": "Asilarkness/testgeniy", "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 "Asilarkness/testgeniy" \ --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": "Asilarkness/testgeniy", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Asilarkness/testgeniy with Docker Model Runner:
docker model run hf.co/Asilarkness/testgeniy
Add RL v2 step20 manifest
Browse files
rl_v2_helpsteer_step20/manifest.json
ADDED
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{
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"folder": "rl_v2_helpsteer_step20",
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"repo": "Asilarkness/testgeniy",
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"checkpoint": "/marimo/testgeniy_rl_real/checkpoints/real_rl_v2_step_0020.pt",
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"version": "testgeniy-v6-real-online-grpo-helpsteer-v2-step20",
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"base_checkpoint": "/marimo/testgeniy_v6_clean/checkpoints/dialogue_sft.pt",
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"real_only_prompts": true,
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"synthetic_prompts": false,
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"mtp": false,
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"algorithm": "online_group_relative_policy_gradient",
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"human_reward": {
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"dataset": "nvidia/HelpSteer2",
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"validation": "OpenAssistant/oasst1 preferences"
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},
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"fixed_suite": {
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"gsm8k_test": 24.0,
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"math500_test": 8.0,
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"arc_challenge_test": 26.0,
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"folio_validation": 29.0,
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"composite": 21.75
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},
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"baseline_v6": {
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"gsm8k_test": 24.0,
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"math500_test": 7.0,
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"arc_challenge_test": 26.0,
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"folio_validation": 29.0,
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"composite": 21.5
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},
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"human_holdouts": {
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"oasst_validation_accuracy": 55.0,
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"helpsteer_wide500_accuracy": 41.6
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},
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"status": "best_measured_candidate_not_primary"
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}
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