Instructions to use vsan/tiny-pickle-35b-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use vsan/tiny-pickle-35b-LoRA with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.6-35B-A3B") model = PeftModel.from_pretrained(base_model, "vsan/tiny-pickle-35b-LoRA") - Transformers
How to use vsan/tiny-pickle-35b-LoRA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="vsan/tiny-pickle-35b-LoRA") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("vsan/tiny-pickle-35b-LoRA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use vsan/tiny-pickle-35b-LoRA with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "vsan/tiny-pickle-35b-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": "vsan/tiny-pickle-35b-LoRA", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/vsan/tiny-pickle-35b-LoRA
- SGLang
How to use vsan/tiny-pickle-35b-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 "vsan/tiny-pickle-35b-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": "vsan/tiny-pickle-35b-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 "vsan/tiny-pickle-35b-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": "vsan/tiny-pickle-35b-LoRA", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use vsan/tiny-pickle-35b-LoRA with Docker Model Runner:
docker model run hf.co/vsan/tiny-pickle-35b-LoRA
| { | |
| "best_global_step": null, | |
| "best_metric": null, | |
| "best_model_checkpoint": null, | |
| "epoch": 0.4819277108433735, | |
| "eval_steps": 500, | |
| "global_step": 20, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "aux_loss": 8.112077713012695, | |
| "entropy": 0.5542473942041397, | |
| "epoch": 0.024096385542168676, | |
| "grad_norm": 12.316938400268555, | |
| "learning_rate": 0.0, | |
| "loss": 4.649446487426758, | |
| "mean_token_accuracy": 0.4230975955724716, | |
| "num_tokens": 3858.0, | |
| "step": 1 | |
| }, | |
| { | |
| "aux_loss": 8.104777336120605, | |
| "entropy": 0.5576090589165688, | |
| "epoch": 0.04819277108433735, | |
| "grad_norm": 11.46682357788086, | |
| "learning_rate": 5e-05, | |
| "loss": 4.360793590545654, | |
| "mean_token_accuracy": 0.4478432685136795, | |
| "num_tokens": 7881.0, | |
| "step": 2 | |
| }, | |
| { | |
| "aux_loss": 8.111183881759644, | |
| "entropy": 0.6309102177619934, | |
| "epoch": 0.07228915662650602, | |
| "grad_norm": 11.137980461120605, | |
| "learning_rate": 0.0001, | |
| "loss": 4.385745048522949, | |
| "mean_token_accuracy": 0.41679511964321136, | |
| "num_tokens": 11760.0, | |
| "step": 3 | |
| }, | |
| { | |
| "aux_loss": 8.115976572036743, | |
| "entropy": 0.8519729971885681, | |
| "epoch": 0.0963855421686747, | |
| "grad_norm": 8.42417049407959, | |
| "learning_rate": 9.924038765061042e-05, | |
| "loss": 3.61301326751709, | |
| "mean_token_accuracy": 0.4827836826443672, | |
| "num_tokens": 15787.0, | |
| "step": 4 | |
| }, | |
| { | |
| "aux_loss": 8.109588623046875, | |
| "entropy": 1.0264470428228378, | |
| "epoch": 0.12048192771084337, | |
| "grad_norm": 6.576476573944092, | |
| "learning_rate": 9.698463103929542e-05, | |
| "loss": 3.2094621658325195, | |
| "mean_token_accuracy": 0.49186357110738754, | |
| "num_tokens": 19714.0, | |
| "step": 5 | |
| }, | |
| { | |
| "aux_loss": 8.101800441741943, | |
| "entropy": 0.9288285374641418, | |
| "epoch": 0.14457831325301204, | |
| "grad_norm": 3.9594063758850098, | |
| "learning_rate": 9.330127018922194e-05, | |
| "loss": 2.2841343879699707, | |
| "mean_token_accuracy": 0.6183864176273346, | |
| "num_tokens": 23795.0, | |
| "step": 6 | |
| }, | |
| { | |
| "aux_loss": 8.114001750946045, | |
| "entropy": 1.2128139585256577, | |
| "epoch": 0.1686746987951807, | |
| "grad_norm": 6.381528377532959, | |
| "learning_rate": 8.83022221559489e-05, | |
| "loss": 2.5765533447265625, | |
| "mean_token_accuracy": 0.556639589369297, | |
| "num_tokens": 27782.0, | |
| "step": 7 | |
| }, | |
| { | |
| "aux_loss": 8.114900350570679, | |
| "entropy": 1.2565034925937653, | |
| "epoch": 0.1927710843373494, | |
| "grad_norm": 7.642035961151123, | |
| "learning_rate": 8.213938048432697e-05, | |
| "loss": 2.305990219116211, | |
| "mean_token_accuracy": 0.5857522785663605, | |
| "num_tokens": 31747.0, | |
| "step": 8 | |
| }, | |
| { | |
| "aux_loss": 8.110223054885864, | |
| "entropy": 1.3893296420574188, | |
| "epoch": 0.21686746987951808, | |
| "grad_norm": 3.114738941192627, | |
| "learning_rate": 7.500000000000001e-05, | |
| "loss": 2.2381560802459717, | |
| "mean_token_accuracy": 0.5757552534341812, | |
| "num_tokens": 35843.0, | |
| "step": 9 | |
| }, | |
| { | |
| "aux_loss": 8.100109577178955, | |
| "entropy": 1.3012381047010422, | |
| "epoch": 0.24096385542168675, | |
| "grad_norm": 2.429396390914917, | |
| "learning_rate": 6.710100716628344e-05, | |
| "loss": 1.8264377117156982, | |
| "mean_token_accuracy": 0.6413185894489288, | |
| "num_tokens": 39849.0, | |
| "step": 10 | |
| }, | |
| { | |
| "aux_loss": 8.10316777229309, | |
| "entropy": 1.3610867857933044, | |
| "epoch": 0.26506024096385544, | |
| "grad_norm": 2.0293450355529785, | |
| "learning_rate": 5.868240888334653e-05, | |
| "loss": 1.8157933950424194, | |
| "mean_token_accuracy": 0.6315982639789581, | |
| "num_tokens": 43801.0, | |
| "step": 11 | |
| }, | |
| { | |
| "aux_loss": 8.107757568359375, | |
| "entropy": 1.3844908773899078, | |
| "epoch": 0.2891566265060241, | |
| "grad_norm": 2.0684814453125, | |
| "learning_rate": 5e-05, | |
| "loss": 1.7225821018218994, | |
| "mean_token_accuracy": 0.6499734818935394, | |
| "num_tokens": 47890.0, | |
| "step": 12 | |
| }, | |
| { | |
| "aux_loss": 8.115497589111328, | |
| "entropy": 1.3100078850984573, | |
| "epoch": 0.3132530120481928, | |
| "grad_norm": 1.7339991331100464, | |
| "learning_rate": 4.131759111665349e-05, | |
| "loss": 1.5674974918365479, | |
| "mean_token_accuracy": 0.6856758892536163, | |
| "num_tokens": 51984.0, | |
| "step": 13 | |
| }, | |
| { | |
| "aux_loss": 8.117025375366211, | |
| "entropy": 1.4904241859912872, | |
| "epoch": 0.3373493975903614, | |
| "grad_norm": 2.1457736492156982, | |
| "learning_rate": 3.289899283371657e-05, | |
| "loss": 1.7369965314865112, | |
| "mean_token_accuracy": 0.6343775242567062, | |
| "num_tokens": 55908.0, | |
| "step": 14 | |
| }, | |
| { | |
| "aux_loss": 8.109899997711182, | |
| "entropy": 1.2758602499961853, | |
| "epoch": 0.3614457831325301, | |
| "grad_norm": 1.6773629188537598, | |
| "learning_rate": 2.500000000000001e-05, | |
| "loss": 1.4753482341766357, | |
| "mean_token_accuracy": 0.6864070445299149, | |
| "num_tokens": 59886.0, | |
| "step": 15 | |
| }, | |
| { | |
| "aux_loss": 8.102123498916626, | |
| "entropy": 1.4675858318805695, | |
| "epoch": 0.3855421686746988, | |
| "grad_norm": 1.817078709602356, | |
| "learning_rate": 1.7860619515673033e-05, | |
| "loss": 1.649685025215149, | |
| "mean_token_accuracy": 0.6493639498949051, | |
| "num_tokens": 63900.0, | |
| "step": 16 | |
| }, | |
| { | |
| "aux_loss": 8.11583948135376, | |
| "entropy": 1.6035236716270447, | |
| "epoch": 0.40963855421686746, | |
| "grad_norm": 2.301260471343994, | |
| "learning_rate": 1.1697777844051105e-05, | |
| "loss": 1.7476608753204346, | |
| "mean_token_accuracy": 0.6294074505567551, | |
| "num_tokens": 67857.0, | |
| "step": 17 | |
| }, | |
| { | |
| "aux_loss": 8.110026121139526, | |
| "entropy": 1.5781865417957306, | |
| "epoch": 0.43373493975903615, | |
| "grad_norm": 1.9237574338912964, | |
| "learning_rate": 6.698729810778065e-06, | |
| "loss": 1.7121555805206299, | |
| "mean_token_accuracy": 0.6350390315055847, | |
| "num_tokens": 71882.0, | |
| "step": 18 | |
| }, | |
| { | |
| "aux_loss": 8.128801584243774, | |
| "entropy": 1.5062502324581146, | |
| "epoch": 0.4578313253012048, | |
| "grad_norm": 2.0424976348876953, | |
| "learning_rate": 3.0153689607045845e-06, | |
| "loss": 1.6763399839401245, | |
| "mean_token_accuracy": 0.6374592185020447, | |
| "num_tokens": 75767.0, | |
| "step": 19 | |
| }, | |
| { | |
| "aux_loss": 8.109554052352905, | |
| "entropy": 1.2872552573680878, | |
| "epoch": 0.4819277108433735, | |
| "grad_norm": 1.4331955909729004, | |
| "learning_rate": 7.596123493895991e-07, | |
| "loss": 1.464625358581543, | |
| "mean_token_accuracy": 0.6907707750797272, | |
| "num_tokens": 79715.0, | |
| "step": 20 | |
| } | |
| ], | |
| "logging_steps": 1, | |
| "max_steps": 20, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 1, | |
| "save_steps": 10, | |
| "stateful_callbacks": { | |
| "TrainerControl": { | |
| "args": { | |
| "should_epoch_stop": false, | |
| "should_evaluate": false, | |
| "should_log": false, | |
| "should_save": true, | |
| "should_training_stop": true | |
| }, | |
| "attributes": {} | |
| } | |
| }, | |
| "total_flos": 1.633858114438272e+16, | |
| "train_batch_size": 1, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |