Text Generation
Transformers
TensorBoard
Safetensors
openelm
trl
kto
alignment-handbook
Generated from Trainer
conversational
custom_code
Instructions to use CharlesLi/OpenELM-1_1B-KTO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CharlesLi/OpenELM-1_1B-KTO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="CharlesLi/OpenELM-1_1B-KTO", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("CharlesLi/OpenELM-1_1B-KTO", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use CharlesLi/OpenELM-1_1B-KTO with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "CharlesLi/OpenELM-1_1B-KTO" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "CharlesLi/OpenELM-1_1B-KTO", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/CharlesLi/OpenELM-1_1B-KTO
- SGLang
How to use CharlesLi/OpenELM-1_1B-KTO 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 "CharlesLi/OpenELM-1_1B-KTO" \ --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": "CharlesLi/OpenELM-1_1B-KTO", "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 "CharlesLi/OpenELM-1_1B-KTO" \ --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": "CharlesLi/OpenELM-1_1B-KTO", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use CharlesLi/OpenELM-1_1B-KTO with Docker Model Runner:
docker model run hf.co/CharlesLi/OpenELM-1_1B-KTO
File size: 11,947 Bytes
a1c0da7 bb7f0c0 a1c0da7 bb7f0c0 a1c0da7 bb7f0c0 a1c0da7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 | ---
library_name: transformers
tags:
- trl
- kto
- alignment-handbook
- generated_from_trainer
model-index:
- name: OpenELM-1_1B-KTO
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# OpenELM-1_1B-KTO
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Kl: 0.0
- Logits/chosen: -1428926080.0
- Logits/rejected: -1154165888.0
- Logps/chosen: -548.5443
- Logps/rejected: -840.7200
- Loss: 0.4491
- Rewards/chosen: -2.1686
- Rewards/margins: 3.2859
- Rewards/rejected: -5.4545
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Kl | Logits/chosen | Logits/rejected | Logps/chosen | Logps/rejected | Validation Loss | Rewards/chosen | Rewards/margins | Rewards/rejected |
|:-------------:|:------:|:----:|:---:|:-------------:|:---------------:|:------------:|:--------------:|:---------------:|:--------------:|:---------------:|:----------------:|
| 0.4859 | 0.0523 | 100 | 0.0 | -3175687424.0 | -3128284928.0 | -393.0411 | -370.7767 | 0.4855 | -0.6136 | 0.1415 | -0.7551 |
| 0.4556 | 0.1047 | 200 | 0.0 | -3518155520.0 | -3502177280.0 | -452.2593 | -491.0910 | 0.4658 | -1.2023 | 0.7579 | -1.9602 |
| 0.4658 | 0.1570 | 300 | 0.0 | -3454242304.0 | -3428943360.0 | -416.2217 | -439.7414 | 0.4630 | -0.8430 | 0.6032 | -1.4462 |
| 0.4543 | 0.2094 | 400 | 0.0 | -3808428032.0 | -3728536576.0 | -562.5413 | -589.5574 | 0.4728 | -2.3096 | 0.6357 | -2.9453 |
| 0.4445 | 0.2617 | 500 | 0.0 | -3128418048.0 | -2977955840.0 | -534.3256 | -585.3565 | 0.4657 | -2.0271 | 0.8745 | -2.9015 |
| 0.4654 | 0.3141 | 600 | 0.0 | -3596449280.0 | -3444389120.0 | -529.1321 | -582.2695 | 0.4658 | -1.9723 | 0.8963 | -2.8686 |
| 0.4517 | 0.3664 | 700 | 0.0 | -3631068928.0 | -3583666688.0 | -452.7501 | -492.3958 | 0.4690 | -1.2099 | 0.7624 | -1.9723 |
| 0.4701 | 0.4187 | 800 | 0.0 | -3269426688.0 | -3207910144.0 | -550.3810 | -656.9627 | 0.4595 | -2.1877 | 1.4299 | -3.6176 |
| 0.4711 | 0.4711 | 900 | 0.0 | -3022695168.0 | -3008713984.0 | -592.4354 | -758.0388 | 0.4626 | -2.6066 | 2.0224 | -4.6290 |
| 0.4534 | 0.5234 | 1000 | 0.0 | -2621240320.0 | -2359728640.0 | -548.9560 | -656.3580 | 0.4594 | -2.1704 | 1.4414 | -3.6118 |
| 0.4428 | 0.5758 | 1100 | 0.0 | -2962243840.0 | -2838944512.0 | -587.9386 | -759.0254 | 0.4583 | -2.5622 | 2.0794 | -4.6416 |
| 0.4619 | 0.6281 | 1200 | 0.0 | -2887944704.0 | -2875961088.0 | -570.1098 | -742.3173 | 0.4549 | -2.3843 | 2.0891 | -4.4734 |
| 0.4627 | 0.6805 | 1300 | 0.0 | -2942404096.0 | -2700332800.0 | -705.3934 | -1037.3665 | 0.4565 | -3.7379 | 3.6828 | -7.4207 |
| 0.4622 | 0.7328 | 1400 | 0.0 | -3010711296.0 | -2812979968.0 | -783.2637 | -1089.1775 | 0.4620 | -4.5181 | 3.4185 | -7.9366 |
| 0.4571 | 0.7851 | 1500 | 0.0 | -2759985152.0 | -2638283776.0 | -567.8931 | -773.6330 | 0.4572 | -2.3622 | 2.4227 | -4.7849 |
| 0.4714 | 0.8375 | 1600 | 0.0 | -2749732352.0 | -2697137152.0 | -526.0604 | -662.9458 | 0.4618 | -1.9416 | 1.7369 | -3.6785 |
| 0.4266 | 0.8898 | 1700 | 0.0 | -1904080896.0 | -1675191680.0 | -554.2761 | -683.2819 | 0.4548 | -2.2239 | 1.6573 | -3.8812 |
| 0.449 | 0.9422 | 1800 | 0.0 | -2063198080.0 | -1781980032.0 | -630.7531 | -780.4754 | 0.4612 | -2.9899 | 1.8639 | -4.8538 |
| 0.4773 | 0.9945 | 1900 | 0.0 | -2405932544.0 | -2133635840.0 | -658.1771 | -792.9826 | 0.4612 | -3.2661 | 1.7145 | -4.9806 |
| 0.4654 | 1.0468 | 2000 | 0.0 | -2678495744.0 | -2597272832.0 | -528.9421 | -616.7041 | 0.4568 | -1.9690 | 1.2455 | -3.2144 |
| 0.4228 | 1.0992 | 2100 | 0.0 | -1897423232.0 | -1554289280.0 | -605.4824 | -827.4172 | 0.4540 | -2.7379 | 2.5883 | -5.3262 |
| 0.4094 | 1.1515 | 2200 | 0.0 | -1938966784.0 | -1658281344.0 | -495.0579 | -585.3565 | 0.4561 | -1.6318 | 1.2711 | -2.9029 |
| 0.3779 | 1.2039 | 2300 | 0.0 | -2399674624.0 | -2125380352.0 | -514.6284 | -627.5883 | 0.4564 | -1.8295 | 1.4960 | -3.3256 |
| 0.3731 | 1.2562 | 2400 | 0.0 | -1886105216.0 | -1661210752.0 | -496.7679 | -605.2153 | 0.4578 | -1.6493 | 1.4530 | -3.1023 |
| 0.3538 | 1.3086 | 2500 | 0.0 | -1523131520.0 | -1173539584.0 | -520.2969 | -641.4639 | 0.4578 | -1.8841 | 1.5789 | -3.4630 |
| 0.3699 | 1.3609 | 2600 | 0.0 | -2620041984.0 | -2228706560.0 | -464.2454 | -571.5127 | 0.4552 | -1.3250 | 1.4383 | -2.7633 |
| 0.3293 | 1.4132 | 2700 | 0.0 | -1547698176.0 | -1145178112.0 | -559.4696 | -805.1397 | 0.4508 | -2.2760 | 2.8229 | -5.0990 |
| 0.3376 | 1.4656 | 2800 | 0.0 | -1543770240.0 | -1201035648.0 | -495.7229 | -643.6280 | 0.4576 | -1.6388 | 1.8453 | -3.4841 |
| 0.3545 | 1.5179 | 2900 | 0.0 | -1516407296.0 | -1264482816.0 | -736.2058 | -1167.2123 | 0.4523 | -4.0433 | 4.6733 | -8.7166 |
| 0.3399 | 1.5703 | 3000 | 0.0 | -2308331776.0 | -2173847808.0 | -634.2682 | -983.0731 | 0.4497 | -3.0224 | 3.8548 | -6.8772 |
| 0.3429 | 1.6226 | 3100 | 0.0 | -2065728000.0 | -1775322368.0 | -641.7100 | -945.9015 | 0.4497 | -3.1008 | 3.4052 | -6.5060 |
| 0.3005 | 1.6750 | 3200 | 0.0 | -2172250112.0 | -2024051328.0 | -515.8318 | -719.3396 | 0.4492 | -1.8422 | 2.3998 | -4.2420 |
| 0.3468 | 1.7273 | 3300 | 0.0 | -2299277568.0 | -2052279552.0 | -650.1019 | -1102.9896 | 0.4503 | -3.1821 | 4.8952 | -8.0773 |
| 0.3361 | 1.7796 | 3400 | 0.0 | -1953080960.0 | -1726854912.0 | -586.8936 | -953.3486 | 0.4488 | -2.5504 | 4.0314 | -6.5818 |
| 0.3405 | 1.8320 | 3500 | 0.0 | -1600359936.0 | -1368940928.0 | -595.8555 | -917.2273 | 0.4473 | -2.6417 | 3.5806 | -6.2223 |
| 0.362 | 1.8843 | 3600 | 0.0 | -1622263552.0 | -1444837888.0 | -594.8738 | -933.2352 | 0.4472 | -2.6312 | 3.7478 | -6.3789 |
| 0.3153 | 1.9367 | 3700 | 0.0 | -1449431680.0 | -1236653952.0 | -548.1009 | -828.2765 | 0.4482 | -2.1611 | 3.1750 | -5.3362 |
| 0.332 | 1.9890 | 3800 | 0.0 | -1527192704.0 | -1300766848.0 | -517.2568 | -750.3690 | 0.4465 | -1.8534 | 2.6999 | -4.5532 |
| 0.3281 | 2.0414 | 3900 | 0.0 | -1679585792.0 | -1427328256.0 | -596.9639 | -954.6852 | 0.4463 | -2.6517 | 3.9427 | -6.5944 |
| 0.3181 | 2.0937 | 4000 | 0.0 | -1560081408.0 | -1263351040.0 | -525.1103 | -727.0094 | 0.4486 | -1.9321 | 2.3847 | -4.3169 |
| 0.2603 | 2.1460 | 4100 | 0.0 | -1459418112.0 | -1138054528.0 | -524.6037 | -721.5356 | 0.4512 | -1.9273 | 2.3376 | -4.2649 |
| 0.2388 | 2.1984 | 4200 | 0.0 | -1377462656.0 | -1113288064.0 | -484.2593 | -613.2352 | 0.4556 | -1.5242 | 1.6601 | -3.1844 |
| 0.224 | 2.2507 | 4300 | 0.0 | -1391976320.0 | -1133061248.0 | -479.9842 | -590.8304 | 0.4576 | -1.4813 | 1.4770 | -2.9584 |
| 0.26 | 2.3031 | 4400 | 0.0 | -1215682432.0 | -961427712.0 | -496.7046 | -633.5714 | 0.4562 | -1.6511 | 1.7328 | -3.3839 |
| 0.2234 | 2.3554 | 4500 | 0.0 | -1145577600.0 | -884432256.0 | -540.8808 | -735.6340 | 0.4557 | -2.0918 | 2.3138 | -4.4056 |
| 0.235 | 2.4077 | 4600 | 0.0 | -1404625792.0 | -1132328960.0 | -488.9302 | -651.3615 | 0.4559 | -1.5702 | 1.9911 | -3.5613 |
| 0.2246 | 2.4601 | 4700 | 0.0 | -1378527872.0 | -1094446976.0 | -506.0782 | -691.9065 | 0.4523 | -1.7423 | 2.2245 | -3.9668 |
| 0.24 | 2.5124 | 4800 | 0.0 | -1400231808.0 | -1111490560.0 | -509.5299 | -701.2312 | 0.4519 | -1.7776 | 2.2838 | -4.0614 |
| 0.2557 | 2.5648 | 4900 | 0.0 | -1397235840.0 | -1123008256.0 | -528.5304 | -749.2869 | 0.4514 | -1.9623 | 2.5779 | -4.5403 |
| 0.2413 | 2.6171 | 5000 | 0.0 | -1477659904.0 | -1194644352.0 | -527.0421 | -771.0870 | 0.4506 | -1.9521 | 2.8087 | -4.7608 |
| 0.2273 | 2.6695 | 5100 | 0.0 | -1420737280.0 | -1144246016.0 | -524.3503 | -753.7106 | 0.4495 | -1.9271 | 2.6609 | -4.5880 |
| 0.2645 | 2.7218 | 5200 | 0.0 | -1426662528.0 | -1147708032.0 | -529.0688 | -767.9682 | 0.4501 | -1.9730 | 2.7549 | -4.7279 |
| 0.2637 | 2.7741 | 5300 | 0.0 | -1414479104.0 | -1139319424.0 | -551.0460 | -835.7553 | 0.4497 | -2.1932 | 3.2146 | -5.4078 |
| 0.2683 | 2.8265 | 5400 | 0.0 | -1420271232.0 | -1144445824.0 | -552.9777 | -847.9125 | 0.4496 | -2.2117 | 3.3187 | -5.5303 |
| 0.2551 | 2.8788 | 5500 | 0.0 | -1425663872.0 | -1148307200.0 | -551.4577 | -846.3531 | 0.4494 | -2.1969 | 3.3124 | -5.5093 |
| 0.2695 | 2.9312 | 5600 | 0.0 | -1428859520.0 | -1154099328.0 | -548.8293 | -841.0065 | 0.4490 | -2.1721 | 3.2870 | -5.4591 |
| 0.2664 | 2.9835 | 5700 | 0.0 | -1428926080.0 | -1154165888.0 | -548.5443 | -840.7200 | 0.4491 | -2.1686 | 3.2859 | -5.4545 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.3.0
- Datasets 3.0.0
- Tokenizers 0.19.1
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