Instructions to use modrill/qwen3_4b_base_kodcode4o_shortcot_8k_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use modrill/qwen3_4b_base_kodcode4o_shortcot_8k_lora with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="modrill/qwen3_4b_base_kodcode4o_shortcot_8k_lora") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("modrill/qwen3_4b_base_kodcode4o_shortcot_8k_lora", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use modrill/qwen3_4b_base_kodcode4o_shortcot_8k_lora with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "modrill/qwen3_4b_base_kodcode4o_shortcot_8k_lora" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "modrill/qwen3_4b_base_kodcode4o_shortcot_8k_lora", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/modrill/qwen3_4b_base_kodcode4o_shortcot_8k_lora
- SGLang
How to use modrill/qwen3_4b_base_kodcode4o_shortcot_8k_lora 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 "modrill/qwen3_4b_base_kodcode4o_shortcot_8k_lora" \ --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": "modrill/qwen3_4b_base_kodcode4o_shortcot_8k_lora", "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 "modrill/qwen3_4b_base_kodcode4o_shortcot_8k_lora" \ --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": "modrill/qwen3_4b_base_kodcode4o_shortcot_8k_lora", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use modrill/qwen3_4b_base_kodcode4o_shortcot_8k_lora with Docker Model Runner:
docker model run hf.co/modrill/qwen3_4b_base_kodcode4o_shortcot_8k_lora
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| {"current_steps": 20, "total_steps": 3094, "loss": 0.45131635665893555, "lr": 1.2258064516129032e-05, "epoch": 0.006464646464646465, "percentage": 0.65, "elapsed_time": "0:01:08", "remaining_time": "2:55:02"} | |
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| {"current_steps": 40, "total_steps": 3094, "loss": 0.41430253982543946, "lr": 2.5161290322580645e-05, "epoch": 0.01292929292929293, "percentage": 1.29, "elapsed_time": "0:02:10", "remaining_time": "2:45:42"} | |
| {"current_steps": 50, "total_steps": 3094, "loss": 0.399013614654541, "lr": 3.161290322580645e-05, "epoch": 0.01616161616161616, "percentage": 1.62, "elapsed_time": "0:02:40", "remaining_time": "2:42:26"} | |
| {"current_steps": 60, "total_steps": 3094, "loss": 0.394245982170105, "lr": 3.8064516129032254e-05, "epoch": 0.019393939393939394, "percentage": 1.94, "elapsed_time": "0:03:11", "remaining_time": "2:41:14"} | |
| {"current_steps": 70, "total_steps": 3094, "loss": 0.4129539966583252, "lr": 4.451612903225807e-05, "epoch": 0.022626262626262626, "percentage": 2.26, "elapsed_time": "0:03:40", "remaining_time": "2:38:40"} | |
| {"current_steps": 80, "total_steps": 3094, "loss": 0.40581393241882324, "lr": 5.096774193548387e-05, "epoch": 0.02585858585858586, "percentage": 2.59, "elapsed_time": "0:04:10", "remaining_time": "2:37:17"} | |
| {"current_steps": 90, "total_steps": 3094, "loss": 0.381392502784729, "lr": 5.7419354838709685e-05, "epoch": 0.02909090909090909, "percentage": 2.91, "elapsed_time": "0:04:40", "remaining_time": "2:35:48"} | |
| {"current_steps": 100, "total_steps": 3094, "loss": 0.39757261276245115, "lr": 6.387096774193548e-05, "epoch": 0.03232323232323232, "percentage": 3.23, "elapsed_time": "0:05:09", "remaining_time": "2:34:30"} | |
| {"current_steps": 110, "total_steps": 3094, "loss": 0.38897051811218264, "lr": 7.03225806451613e-05, "epoch": 0.035555555555555556, "percentage": 3.56, "elapsed_time": "0:05:39", "remaining_time": "2:33:29"} | |
| {"current_steps": 120, "total_steps": 3094, "loss": 0.38843908309936526, "lr": 7.67741935483871e-05, "epoch": 0.03878787878787879, "percentage": 3.88, "elapsed_time": "0:06:08", "remaining_time": "2:32:12"} | |
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| {"current_steps": 170, "total_steps": 3094, "loss": 0.38610661029815674, "lr": 9.999440128258112e-05, "epoch": 0.05494949494949495, "percentage": 5.49, "elapsed_time": "0:08:33", "remaining_time": "2:27:06"} | |
| {"current_steps": 180, "total_steps": 3094, "loss": 0.3945873975753784, "lr": 9.998354722168459e-05, "epoch": 0.05818181818181818, "percentage": 5.82, "elapsed_time": "0:09:02", "remaining_time": "2:26:16"} | |
| {"current_steps": 190, "total_steps": 3094, "loss": 0.4054004669189453, "lr": 9.996698201151175e-05, "epoch": 0.061414141414141414, "percentage": 6.14, "elapsed_time": "0:09:30", "remaining_time": "2:25:16"} | |
| {"current_steps": 200, "total_steps": 3094, "loss": 0.3861499786376953, "lr": 9.994470754481315e-05, "epoch": 0.06464646464646465, "percentage": 6.46, "elapsed_time": "0:10:00", "remaining_time": "2:24:42"} | |
| {"current_steps": 210, "total_steps": 3094, "loss": 0.39889438152313234, "lr": 9.991672636668239e-05, "epoch": 0.06787878787878789, "percentage": 6.79, "elapsed_time": "0:10:37", "remaining_time": "2:25:53"} | |
| {"current_steps": 220, "total_steps": 3094, "loss": 0.37990422248840333, "lr": 9.988304167426519e-05, "epoch": 0.07111111111111111, "percentage": 7.11, "elapsed_time": "0:11:06", "remaining_time": "2:25:11"} | |
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| {"current_steps": 310, "total_steps": 3094, "loss": 0.4039336681365967, "lr": 9.932407099666608e-05, "epoch": 0.10020202020202021, "percentage": 10.02, "elapsed_time": "0:15:25", "remaining_time": "2:18:31"} | |
| {"current_steps": 320, "total_steps": 3094, "loss": 0.3808545351028442, "lr": 9.923367009895274e-05, "epoch": 0.10343434343434343, "percentage": 10.34, "elapsed_time": "0:15:54", "remaining_time": "2:17:56"} | |
| {"current_steps": 330, "total_steps": 3094, "loss": 0.3846753597259521, "lr": 9.913764373336079e-05, "epoch": 0.10666666666666667, "percentage": 10.67, "elapsed_time": "0:16:23", "remaining_time": "2:17:21"} | |
| {"current_steps": 340, "total_steps": 3094, "loss": 0.3809442281723022, "lr": 9.903600287191875e-05, "epoch": 0.1098989898989899, "percentage": 10.99, "elapsed_time": "0:16:51", "remaining_time": "2:16:35"} | |
| {"current_steps": 350, "total_steps": 3094, "loss": 0.39042062759399415, "lr": 9.892875912817079e-05, "epoch": 0.11313131313131314, "percentage": 11.31, "elapsed_time": "0:17:20", "remaining_time": "2:15:55"} | |
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| {"current_steps": 440, "total_steps": 3094, "loss": 0.38375401496887207, "lr": 9.771366768261696e-05, "epoch": 0.14222222222222222, "percentage": 14.22, "elapsed_time": "0:21:48", "remaining_time": "2:11:31"} | |
| {"current_steps": 450, "total_steps": 3094, "loss": 0.3801938533782959, "lr": 9.755117395152689e-05, "epoch": 0.14545454545454545, "percentage": 14.54, "elapsed_time": "0:22:19", "remaining_time": "2:11:08"} | |
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| {"current_steps": 510, "total_steps": 3094, "loss": 0.38756704330444336, "lr": 9.646280700585185e-05, "epoch": 0.16484848484848486, "percentage": 16.48, "elapsed_time": "0:25:09", "remaining_time": "2:07:29"} | |
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| {"current_steps": 530, "total_steps": 3094, "loss": 0.38026604652404783, "lr": 9.605731740511022e-05, "epoch": 0.1713131313131313, "percentage": 17.13, "elapsed_time": "0:26:06", "remaining_time": "2:06:20"} | |
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| {"current_steps": 560, "total_steps": 3094, "loss": 0.39109277725219727, "lr": 9.540967565732937e-05, "epoch": 0.181010101010101, "percentage": 18.1, "elapsed_time": "0:27:34", "remaining_time": "2:04:46"} | |
| {"current_steps": 570, "total_steps": 3094, "loss": 0.38657331466674805, "lr": 9.51833845168121e-05, "epoch": 0.18424242424242424, "percentage": 18.42, "elapsed_time": "0:28:02", "remaining_time": "2:04:11"} | |
| {"current_steps": 580, "total_steps": 3094, "loss": 0.375126314163208, "lr": 9.495193069641057e-05, "epoch": 0.1874747474747475, "percentage": 18.75, "elapsed_time": "0:28:31", "remaining_time": "2:03:39"} | |
| {"current_steps": 590, "total_steps": 3094, "loss": 0.3850594997406006, "lr": 9.47153406421734e-05, "epoch": 0.1907070707070707, "percentage": 19.07, "elapsed_time": "0:28:59", "remaining_time": "2:03:03"} | |
| {"current_steps": 600, "total_steps": 3094, "loss": 0.3871599674224854, "lr": 9.447364138701823e-05, "epoch": 0.19393939393939394, "percentage": 19.39, "elapsed_time": "0:29:28", "remaining_time": "2:02:31"} | |
| {"current_steps": 610, "total_steps": 3094, "loss": 0.37601659297943113, "lr": 9.422686054764302e-05, "epoch": 0.19717171717171716, "percentage": 19.72, "elapsed_time": "0:30:04", "remaining_time": "2:02:27"} | |
| {"current_steps": 620, "total_steps": 3094, "loss": 0.3801377773284912, "lr": 9.397502632137055e-05, "epoch": 0.20040404040404042, "percentage": 20.04, "elapsed_time": "0:30:33", "remaining_time": "2:01:58"} | |
| {"current_steps": 630, "total_steps": 3094, "loss": 0.37289042472839357, "lr": 9.371816748292641e-05, "epoch": 0.20363636363636364, "percentage": 20.36, "elapsed_time": "0:31:02", "remaining_time": "2:01:23"} | |
| {"current_steps": 640, "total_steps": 3094, "loss": 0.3836984395980835, "lr": 9.345631338115141e-05, "epoch": 0.20686868686868687, "percentage": 20.69, "elapsed_time": "0:31:30", "remaining_time": "2:00:48"} | |
| {"current_steps": 650, "total_steps": 3094, "loss": 0.3835611820220947, "lr": 9.318949393564807e-05, "epoch": 0.2101010101010101, "percentage": 21.01, "elapsed_time": "0:32:00", "remaining_time": "2:00:22"} | |
| {"current_steps": 660, "total_steps": 3094, "loss": 0.3856090545654297, "lr": 9.291773963336193e-05, "epoch": 0.21333333333333335, "percentage": 21.33, "elapsed_time": "0:32:29", "remaining_time": "1:59:49"} | |
| {"current_steps": 670, "total_steps": 3094, "loss": 0.3813042163848877, "lr": 9.264108152509816e-05, "epoch": 0.21656565656565657, "percentage": 21.65, "elapsed_time": "0:32:57", "remaining_time": "1:59:15"} | |
| {"current_steps": 680, "total_steps": 3094, "loss": 0.3917116165161133, "lr": 9.235955122197368e-05, "epoch": 0.2197979797979798, "percentage": 21.98, "elapsed_time": "0:33:26", "remaining_time": "1:58:43"} | |
| {"current_steps": 690, "total_steps": 3094, "loss": 0.38028013706207275, "lr": 9.207318089180524e-05, "epoch": 0.22303030303030302, "percentage": 22.3, "elapsed_time": "0:33:54", "remaining_time": "1:58:08"} | |
| {"current_steps": 700, "total_steps": 3094, "loss": 0.37664792537689207, "lr": 9.178200325543384e-05, "epoch": 0.22626262626262628, "percentage": 22.62, "elapsed_time": "0:34:23", "remaining_time": "1:57:36"} | |
| {"current_steps": 710, "total_steps": 3094, "loss": 0.36904723644256593, "lr": 9.148605158298621e-05, "epoch": 0.2294949494949495, "percentage": 22.95, "elapsed_time": "0:34:52", "remaining_time": "1:57:05"} | |
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