Instructions to use bobbyzhong/qwen2.5-7b-grpo-codepress-checkpoint30-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use bobbyzhong/qwen2.5-7b-grpo-codepress-checkpoint30-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("bobbyzhong/qwen2.5-7b-codepress-sft-v2-merged") model = PeftModel.from_pretrained(base_model, "bobbyzhong/qwen2.5-7b-grpo-codepress-checkpoint30-lora") - Transformers
How to use bobbyzhong/qwen2.5-7b-grpo-codepress-checkpoint30-lora with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="bobbyzhong/qwen2.5-7b-grpo-codepress-checkpoint30-lora") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("bobbyzhong/qwen2.5-7b-grpo-codepress-checkpoint30-lora", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use bobbyzhong/qwen2.5-7b-grpo-codepress-checkpoint30-lora with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "bobbyzhong/qwen2.5-7b-grpo-codepress-checkpoint30-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": "bobbyzhong/qwen2.5-7b-grpo-codepress-checkpoint30-lora", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/bobbyzhong/qwen2.5-7b-grpo-codepress-checkpoint30-lora
- SGLang
How to use bobbyzhong/qwen2.5-7b-grpo-codepress-checkpoint30-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 "bobbyzhong/qwen2.5-7b-grpo-codepress-checkpoint30-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": "bobbyzhong/qwen2.5-7b-grpo-codepress-checkpoint30-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 "bobbyzhong/qwen2.5-7b-grpo-codepress-checkpoint30-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": "bobbyzhong/qwen2.5-7b-grpo-codepress-checkpoint30-lora", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Unsloth Desktop
- Docker Model Runner
How to use bobbyzhong/qwen2.5-7b-grpo-codepress-checkpoint30-lora with Docker Model Runner:
docker model run hf.co/bobbyzhong/qwen2.5-7b-grpo-codepress-checkpoint30-lora
Download trainer_state.json from bobbyzhong/qwen2.5-7b-grpo-codepress-checkpoint30-lora: direct link, hf CLI and curl.
- Browser
- Download file 8.24 kB
-
https://huggingface.co/bobbyzhong/qwen2.5-7b-grpo-codepress-checkpoint30-lora/resolve/main/trainer_state.json
- Command line
-
hf download hf://bobbyzhong/qwen2.5-7b-grpo-codepress-checkpoint30-lora/trainer_state.json
-
curl -L -o trainer_state.json https://huggingface.co/bobbyzhong/qwen2.5-7b-grpo-codepress-checkpoint30-lora/resolve/main/trainer_state.json
8.24 kB
| { | |
| "best_global_step": null, | |
| "best_metric": null, | |
| "best_model_checkpoint": null, | |
| "epoch": 0.410958904109589, | |
| "eval_steps": 500, | |
| "global_step": 30, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "completion_length": 499.4, | |
| "completions/clipped_ratio": 0.0, | |
| "completions/max_length": 499.4, | |
| "completions/max_terminated_length": 499.4, | |
| "completions/mean_length": 348.35, | |
| "completions/mean_terminated_length": 348.35, | |
| "completions/min_length": 220.2, | |
| "completions/min_terminated_length": 220.2, | |
| "epoch": 0.0684931506849315, | |
| "frac_reward_zero_std": 0.0, | |
| "grad_norm": 0.1234186515212059, | |
| "kl": 0.00031561641953885554, | |
| "learning_rate": 2.0000000000000003e-06, | |
| "loss": 0.0, | |
| "num_tokens": 171527.0, | |
| "reward": 3.540583372116089, | |
| "reward_std": 0.7447549998760223, | |
| "rewards/llm_judge_reward/mean": 0.475, | |
| "rewards/llm_judge_reward/std": 0.13164966106414794, | |
| "rewards/search_replace_reward/mean": 0.4849999964237213, | |
| "rewards/search_replace_reward/std": 0.35137809067964554, | |
| "rewards/tailwind_validation_reward/mean": 0.9, | |
| "rewards/tailwind_validation_reward/std": 0.2, | |
| "rewards/valid_reasoning_reward/mean": 1.0, | |
| "rewards/valid_reasoning_reward/std": 0.0, | |
| "rewards/valid_schema_reward/mean": 0.6805833339691162, | |
| "rewards/valid_schema_reward/std": 0.21482648253440856, | |
| "step": 5 | |
| }, | |
| { | |
| "completion_length": 467.2, | |
| "completions/clipped_ratio": 0.0, | |
| "completions/max_length": 467.2, | |
| "completions/max_terminated_length": 467.2, | |
| "completions/mean_length": 253.5, | |
| "completions/mean_terminated_length": 253.5, | |
| "completions/min_length": 131.2, | |
| "completions/min_terminated_length": 131.2, | |
| "epoch": 0.136986301369863, | |
| "frac_reward_zero_std": 0.0, | |
| "grad_norm": 0.5772600173950195, | |
| "kl": 0.0006777669652365149, | |
| "learning_rate": 4.5e-06, | |
| "loss": 0.0, | |
| "num_tokens": 362177.0, | |
| "reward": 3.0382500171661375, | |
| "reward_std": 0.9091076254844666, | |
| "rewards/llm_judge_reward/mean": 0.6, | |
| "rewards/llm_judge_reward/std": 0.08164966106414795, | |
| "rewards/search_replace_reward/mean": 0.4882499992847443, | |
| "rewards/search_replace_reward/std": 0.4493094146251678, | |
| "rewards/tailwind_validation_reward/mean": 0.75, | |
| "rewards/tailwind_validation_reward/std": 0.2154700517654419, | |
| "rewards/valid_reasoning_reward/mean": 0.4, | |
| "rewards/valid_reasoning_reward/std": 0.0, | |
| "rewards/valid_schema_reward/mean": 0.8, | |
| "rewards/valid_schema_reward/std": 0.3154700517654419, | |
| "step": 10 | |
| }, | |
| { | |
| "completion_length": 298.4, | |
| "completions/clipped_ratio": 0.0, | |
| "completions/max_length": 298.4, | |
| "completions/max_terminated_length": 298.4, | |
| "completions/mean_length": 238.35, | |
| "completions/mean_terminated_length": 238.35, | |
| "completions/min_length": 180.4, | |
| "completions/min_terminated_length": 180.4, | |
| "epoch": 0.2054794520547945, | |
| "frac_reward_zero_std": 0.2, | |
| "grad_norm": 1.8833403373719193e-05, | |
| "kl": 0.0005083533033030108, | |
| "learning_rate": 4.975670171853926e-06, | |
| "loss": 0.0, | |
| "num_tokens": 481628.0, | |
| "reward": 3.7483334064483644, | |
| "reward_std": 0.6907323241233826, | |
| "rewards/llm_judge_reward/mean": 0.725, | |
| "rewards/llm_judge_reward/std": 0.24711971282958983, | |
| "rewards/search_replace_reward/mean": 0.439999994635582, | |
| "rewards/search_replace_reward/std": 0.3035391479730606, | |
| "rewards/tailwind_validation_reward/mean": 0.9, | |
| "rewards/tailwind_validation_reward/std": 0.2, | |
| "rewards/valid_reasoning_reward/mean": 0.8, | |
| "rewards/valid_reasoning_reward/std": 0.0, | |
| "rewards/valid_schema_reward/mean": 0.8833333253860474, | |
| "rewards/valid_schema_reward/std": 0.18164965510368347, | |
| "step": 15 | |
| }, | |
| { | |
| "completion_length": 525.4, | |
| "completions/clipped_ratio": 0.05, | |
| "completions/max_length": 525.4, | |
| "completions/max_terminated_length": 372.8, | |
| "completions/mean_length": 328.65, | |
| "completions/mean_terminated_length": 284.95, | |
| "completions/min_length": 206.2, | |
| "completions/min_terminated_length": 206.2, | |
| "epoch": 0.273972602739726, | |
| "frac_reward_zero_std": 0.0, | |
| "grad_norm": 0.42330870032310486, | |
| "kl": 0.0008551631879527121, | |
| "learning_rate": 4.8776412907378845e-06, | |
| "loss": 0.0, | |
| "num_tokens": 662769.0, | |
| "reward": 3.3797186374664308, | |
| "reward_std": 0.7269979953765869, | |
| "rewards/llm_judge_reward/mean": 0.55, | |
| "rewards/llm_judge_reward/std": 0.1, | |
| "rewards/search_replace_reward/mean": 0.32971862256526946, | |
| "rewards/search_replace_reward/std": 0.3116489231586456, | |
| "rewards/tailwind_validation_reward/mean": 1.0, | |
| "rewards/tailwind_validation_reward/std": 0.0, | |
| "rewards/valid_reasoning_reward/mean": 0.8, | |
| "rewards/valid_reasoning_reward/std": 0.0, | |
| "rewards/valid_schema_reward/mean": 0.7, | |
| "rewards/valid_schema_reward/std": 0.4309401035308838, | |
| "step": 20 | |
| }, | |
| { | |
| "completion_length": 468.8, | |
| "completions/clipped_ratio": 0.0, | |
| "completions/max_length": 468.8, | |
| "completions/max_terminated_length": 468.8, | |
| "completions/mean_length": 314.5, | |
| "completions/mean_terminated_length": 314.5, | |
| "completions/min_length": 193.2, | |
| "completions/min_terminated_length": 193.2, | |
| "epoch": 0.3424657534246575, | |
| "frac_reward_zero_std": 0.0, | |
| "grad_norm": 0.39726072549819946, | |
| "kl": 0.0005920917668845504, | |
| "learning_rate": 4.707368982147318e-06, | |
| "loss": 0.0, | |
| "num_tokens": 820315.0, | |
| "reward": 3.447059488296509, | |
| "reward_std": 0.48202334344387054, | |
| "rewards/llm_judge_reward/mean": 0.575, | |
| "rewards/llm_judge_reward/std": 0.10773502588272095, | |
| "rewards/search_replace_reward/mean": 0.47205952405929563, | |
| "rewards/search_replace_reward/std": 0.37698585391044614, | |
| "rewards/tailwind_validation_reward/mean": 0.7, | |
| "rewards/tailwind_validation_reward/std": 0.3154700517654419, | |
| "rewards/valid_reasoning_reward/mean": 0.8, | |
| "rewards/valid_reasoning_reward/std": 0.0, | |
| "rewards/valid_schema_reward/mean": 0.9, | |
| "rewards/valid_schema_reward/std": 0.2, | |
| "step": 25 | |
| }, | |
| { | |
| "completion_length": 909.8, | |
| "completions/clipped_ratio": 0.15, | |
| "completions/max_length": 909.8, | |
| "completions/max_terminated_length": 407.8, | |
| "completions/mean_length": 493.45, | |
| "completions/mean_terminated_length": 290.6166687011719, | |
| "completions/min_length": 203.2, | |
| "completions/min_terminated_length": 203.2, | |
| "epoch": 0.410958904109589, | |
| "frac_reward_zero_std": 0.2, | |
| "grad_norm": 1.269700050354004, | |
| "kl": 0.0007154575316235424, | |
| "learning_rate": 4.470026884016805e-06, | |
| "loss": 0.0, | |
| "num_tokens": 1025004.0, | |
| "reward": 3.375624990463257, | |
| "reward_std": 0.9000589847564697, | |
| "rewards/llm_judge_reward/mean": 0.525, | |
| "rewards/llm_judge_reward/std": 0.24711971282958983, | |
| "rewards/search_replace_reward/mean": 0.35062500834465027, | |
| "rewards/search_replace_reward/std": 0.3669627845287323, | |
| "rewards/tailwind_validation_reward/mean": 0.85, | |
| "rewards/tailwind_validation_reward/std": 0.2154700517654419, | |
| "rewards/valid_reasoning_reward/mean": 1.0, | |
| "rewards/valid_reasoning_reward/std": 0.0, | |
| "rewards/valid_schema_reward/mean": 0.65, | |
| "rewards/valid_schema_reward/std": 0.48867512941360475, | |
| "step": 30 | |
| } | |
| ], | |
| "logging_steps": 5, | |
| "max_steps": 100, | |
| "num_input_tokens_seen": 1025004, | |
| "num_train_epochs": 2, | |
| "save_steps": 30, | |
| "stateful_callbacks": { | |
| "TrainerControl": { | |
| "args": { | |
| "should_epoch_stop": false, | |
| "should_evaluate": false, | |
| "should_log": false, | |
| "should_save": true, | |
| "should_training_stop": false | |
| }, | |
| "attributes": {} | |
| } | |
| }, | |
| "total_flos": 0.0, | |
| "train_batch_size": 4, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |