Text Generation
Transformers
Safetensors
qwen2
llama-factory
full
Generated from Trainer
conversational
text-generation-inference
Instructions to use AgPerry/Qwen2.5-Coder-7B-Instruct-num06-accumulate_16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AgPerry/Qwen2.5-Coder-7B-Instruct-num06-accumulate_16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="AgPerry/Qwen2.5-Coder-7B-Instruct-num06-accumulate_16") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("AgPerry/Qwen2.5-Coder-7B-Instruct-num06-accumulate_16") model = AutoModelForCausalLM.from_pretrained("AgPerry/Qwen2.5-Coder-7B-Instruct-num06-accumulate_16") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use AgPerry/Qwen2.5-Coder-7B-Instruct-num06-accumulate_16 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "AgPerry/Qwen2.5-Coder-7B-Instruct-num06-accumulate_16" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AgPerry/Qwen2.5-Coder-7B-Instruct-num06-accumulate_16", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/AgPerry/Qwen2.5-Coder-7B-Instruct-num06-accumulate_16
- SGLang
How to use AgPerry/Qwen2.5-Coder-7B-Instruct-num06-accumulate_16 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 "AgPerry/Qwen2.5-Coder-7B-Instruct-num06-accumulate_16" \ --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": "AgPerry/Qwen2.5-Coder-7B-Instruct-num06-accumulate_16", "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 "AgPerry/Qwen2.5-Coder-7B-Instruct-num06-accumulate_16" \ --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": "AgPerry/Qwen2.5-Coder-7B-Instruct-num06-accumulate_16", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use AgPerry/Qwen2.5-Coder-7B-Instruct-num06-accumulate_16 with Docker Model Runner:
docker model run hf.co/AgPerry/Qwen2.5-Coder-7B-Instruct-num06-accumulate_16
| {"current_steps": 10, "total_steps": 3295, "loss": 0.789, "lr": 2.7272727272727274e-07, "epoch": 0.0030350165029022344, "percentage": 0.3, "elapsed_time": "0:15:07", "remaining_time": "3 days, 10:47:43"} | |
| {"current_steps": 20, "total_steps": 3295, "loss": 0.7904, "lr": 5.757575757575758e-07, "epoch": 0.006070033005804469, "percentage": 0.61, "elapsed_time": "0:29:14", "remaining_time": "3 days, 7:49:16"} | |
| {"current_steps": 30, "total_steps": 3295, "loss": 0.744, "lr": 8.787878787878788e-07, "epoch": 0.009105049508706704, "percentage": 0.91, "elapsed_time": "0:43:09", "remaining_time": "3 days, 6:17:00"} | |
| {"current_steps": 40, "total_steps": 3295, "loss": 0.693, "lr": 1.181818181818182e-06, "epoch": 0.012140066011608937, "percentage": 1.21, "elapsed_time": "0:57:52", "remaining_time": "3 days, 6:28:56"} | |
| {"current_steps": 50, "total_steps": 3295, "loss": 0.6656, "lr": 1.484848484848485e-06, "epoch": 0.015175082514511173, "percentage": 1.52, "elapsed_time": "1:05:27", "remaining_time": "2 days, 22:48:31"} | |
| {"current_steps": 60, "total_steps": 3295, "loss": 0.6313, "lr": 1.787878787878788e-06, "epoch": 0.018210099017413408, "percentage": 1.82, "elapsed_time": "1:08:46", "remaining_time": "2 days, 13:47:58"} | |
| {"current_steps": 70, "total_steps": 3295, "loss": 0.6098, "lr": 2.090909090909091e-06, "epoch": 0.021245115520315643, "percentage": 2.12, "elapsed_time": "1:11:52", "remaining_time": "2 days, 7:11:19"} | |
| {"current_steps": 80, "total_steps": 3295, "loss": 0.5885, "lr": 2.393939393939394e-06, "epoch": 0.024280132023217875, "percentage": 2.43, "elapsed_time": "1:14:43", "remaining_time": "2 days, 2:03:12"} | |
| {"current_steps": 90, "total_steps": 3295, "loss": 0.5916, "lr": 2.6969696969696972e-06, "epoch": 0.02731514852612011, "percentage": 2.73, "elapsed_time": "1:18:02", "remaining_time": "1 day, 22:19:15"} | |
| {"current_steps": 100, "total_steps": 3295, "loss": 0.5753, "lr": 3e-06, "epoch": 0.030350165029022345, "percentage": 3.03, "elapsed_time": "1:20:42", "remaining_time": "1 day, 18:58:48"} | |
| {"current_steps": 110, "total_steps": 3295, "loss": 0.5597, "lr": 3.3030303030303033e-06, "epoch": 0.03338518153192458, "percentage": 3.34, "elapsed_time": "1:24:02", "remaining_time": "1 day, 16:33:19"} | |
| {"current_steps": 120, "total_steps": 3295, "loss": 0.5684, "lr": 3.606060606060606e-06, "epoch": 0.036420198034826816, "percentage": 3.64, "elapsed_time": "1:27:04", "remaining_time": "1 day, 14:23:39"} | |
| {"current_steps": 130, "total_steps": 3295, "loss": 0.5569, "lr": 3.90909090909091e-06, "epoch": 0.03945521453772905, "percentage": 3.95, "elapsed_time": "1:29:56", "remaining_time": "1 day, 12:29:46"} | |
| {"current_steps": 140, "total_steps": 3295, "loss": 0.5551, "lr": 4.212121212121212e-06, "epoch": 0.042490231040631286, "percentage": 4.25, "elapsed_time": "1:33:06", "remaining_time": "1 day, 10:58:24"} | |
| {"current_steps": 150, "total_steps": 3295, "loss": 0.5565, "lr": 4.5151515151515155e-06, "epoch": 0.045525247543533515, "percentage": 4.55, "elapsed_time": "1:35:49", "remaining_time": "1 day, 9:28:58"} | |
| {"current_steps": 160, "total_steps": 3295, "loss": 0.5482, "lr": 4.818181818181819e-06, "epoch": 0.04856026404643575, "percentage": 4.86, "elapsed_time": "1:39:06", "remaining_time": "1 day, 8:21:50"} | |
| {"current_steps": 170, "total_steps": 3295, "loss": 0.5482, "lr": 5.121212121212121e-06, "epoch": 0.051595280549337985, "percentage": 5.16, "elapsed_time": "1:42:05", "remaining_time": "1 day, 7:16:38"} | |
| {"current_steps": 180, "total_steps": 3295, "loss": 0.5397, "lr": 5.424242424242425e-06, "epoch": 0.05463029705224022, "percentage": 5.46, "elapsed_time": "1:44:58", "remaining_time": "1 day, 6:16:47"} | |
| {"current_steps": 190, "total_steps": 3295, "loss": 0.5379, "lr": 5.727272727272728e-06, "epoch": 0.057665313555142456, "percentage": 5.77, "elapsed_time": "1:48:10", "remaining_time": "1 day, 5:27:41"} | |
| {"current_steps": 200, "total_steps": 3295, "loss": 0.5487, "lr": 6.030303030303031e-06, "epoch": 0.06070033005804469, "percentage": 6.07, "elapsed_time": "1:50:46", "remaining_time": "1 day, 4:34:15"} | |
| {"current_steps": 210, "total_steps": 3295, "loss": 0.5354, "lr": 6.333333333333333e-06, "epoch": 0.06373534656094693, "percentage": 6.37, "elapsed_time": "1:54:05", "remaining_time": "1 day, 3:55:59"} | |
| {"current_steps": 220, "total_steps": 3295, "loss": 0.5321, "lr": 6.6363636363636375e-06, "epoch": 0.06677036306384916, "percentage": 6.68, "elapsed_time": "1:57:12", "remaining_time": "1 day, 3:18:18"} | |
| {"current_steps": 230, "total_steps": 3295, "loss": 0.5286, "lr": 6.93939393939394e-06, "epoch": 0.0698053795667514, "percentage": 6.98, "elapsed_time": "2:00:02", "remaining_time": "1 day, 2:39:38"} | |
| {"current_steps": 240, "total_steps": 3295, "loss": 0.5277, "lr": 7.242424242424243e-06, "epoch": 0.07284039606965363, "percentage": 7.28, "elapsed_time": "2:03:12", "remaining_time": "1 day, 2:08:24"} | |
| {"current_steps": 250, "total_steps": 3295, "loss": 0.5333, "lr": 7.545454545454546e-06, "epoch": 0.07587541257255587, "percentage": 7.59, "elapsed_time": "2:05:51", "remaining_time": "1 day, 1:32:56"} | |
| {"current_steps": 260, "total_steps": 3295, "loss": 0.5272, "lr": 7.848484848484849e-06, "epoch": 0.0789104290754581, "percentage": 7.89, "elapsed_time": "2:09:08", "remaining_time": "1 day, 1:07:27"} | |
| {"current_steps": 270, "total_steps": 3295, "loss": 0.5283, "lr": 8.151515151515152e-06, "epoch": 0.08194544557836034, "percentage": 8.19, "elapsed_time": "2:12:08", "remaining_time": "1 day, 0:40:30"} | |
| {"current_steps": 280, "total_steps": 3295, "loss": 0.5212, "lr": 8.454545454545455e-06, "epoch": 0.08498046208126257, "percentage": 8.5, "elapsed_time": "2:14:57", "remaining_time": "1 day, 0:13:15"} | |
| {"current_steps": 290, "total_steps": 3295, "loss": 0.5161, "lr": 8.757575757575759e-06, "epoch": 0.08801547858416481, "percentage": 8.8, "elapsed_time": "2:18:12", "remaining_time": "23:52:06"} | |
| {"current_steps": 300, "total_steps": 3295, "loss": 0.5281, "lr": 9.06060606060606e-06, "epoch": 0.09105049508706703, "percentage": 9.1, "elapsed_time": "2:20:51", "remaining_time": "23:26:09"} | |
| {"current_steps": 310, "total_steps": 3295, "loss": 0.5154, "lr": 9.363636363636365e-06, "epoch": 0.09408551158996926, "percentage": 9.41, "elapsed_time": "2:24:02", "remaining_time": "23:07:03"} | |
| {"current_steps": 320, "total_steps": 3295, "loss": 0.5218, "lr": 9.666666666666667e-06, "epoch": 0.0971205280928715, "percentage": 9.71, "elapsed_time": "2:27:05", "remaining_time": "22:47:29"} | |
| {"current_steps": 330, "total_steps": 3295, "loss": 0.5169, "lr": 9.96969696969697e-06, "epoch": 0.10015554459577374, "percentage": 10.02, "elapsed_time": "2:30:00", "remaining_time": "22:27:49"} | |
| {"current_steps": 340, "total_steps": 3295, "loss": 0.5133, "lr": 9.999772661973056e-06, "epoch": 0.10319056109867597, "percentage": 10.32, "elapsed_time": "2:33:14", "remaining_time": "22:11:50"} | |
| {"current_steps": 350, "total_steps": 3295, "loss": 0.52, "lr": 9.99898682866784e-06, "epoch": 0.1062255776015782, "percentage": 10.62, "elapsed_time": "2:35:48", "remaining_time": "21:51:03"} | |
| {"current_steps": 360, "total_steps": 3295, "loss": 0.5008, "lr": 9.997639781643002e-06, "epoch": 0.10926059410448044, "percentage": 10.93, "elapsed_time": "2:39:03", "remaining_time": "21:36:42"} | |
| {"current_steps": 370, "total_steps": 3295, "loss": 0.517, "lr": 9.99573167212544e-06, "epoch": 0.11229561060738268, "percentage": 11.23, "elapsed_time": "2:42:10", "remaining_time": "21:22:01"} | |
| {"current_steps": 380, "total_steps": 3295, "loss": 0.5092, "lr": 9.993262714330009e-06, "epoch": 0.11533062711028491, "percentage": 11.53, "elapsed_time": "2:44:57", "remaining_time": "21:05:23"} | |
| {"current_steps": 390, "total_steps": 3295, "loss": 0.513, "lr": 9.990233185435473e-06, "epoch": 0.11836564361318715, "percentage": 11.84, "elapsed_time": "2:48:05", "remaining_time": "20:52:06"} | |
| {"current_steps": 400, "total_steps": 3295, "loss": 0.5129, "lr": 9.986643425553386e-06, "epoch": 0.12140066011608938, "percentage": 12.14, "elapsed_time": "2:50:45", "remaining_time": "20:35:49"} | |
| {"current_steps": 410, "total_steps": 3295, "loss": 0.5073, "lr": 9.98249383768991e-06, "epoch": 0.12443567661899162, "percentage": 12.44, "elapsed_time": "2:53:54", "remaining_time": "20:23:41"} | |
| {"current_steps": 420, "total_steps": 3295, "loss": 0.5088, "lr": 9.977784887700572e-06, "epoch": 0.12747069312189385, "percentage": 12.75, "elapsed_time": "2:56:55", "remaining_time": "20:11:08"} | |
| {"current_steps": 430, "total_steps": 3295, "loss": 0.4991, "lr": 9.972517104237961e-06, "epoch": 0.13050570962479607, "percentage": 13.05, "elapsed_time": "2:59:43", "remaining_time": "19:57:30"} | |
| {"current_steps": 440, "total_steps": 3295, "loss": 0.506, "lr": 9.966691078692386e-06, "epoch": 0.13354072612769832, "percentage": 13.35, "elapsed_time": "3:02:57", "remaining_time": "19:47:10"} | |
| {"current_steps": 450, "total_steps": 3295, "loss": 0.5025, "lr": 9.960307465125472e-06, "epoch": 0.13657574263060054, "percentage": 13.66, "elapsed_time": "3:05:37", "remaining_time": "19:33:36"} | |
| {"current_steps": 460, "total_steps": 3295, "loss": 0.4976, "lr": 9.953366980196746e-06, "epoch": 0.1396107591335028, "percentage": 13.96, "elapsed_time": "3:08:55", "remaining_time": "19:24:19"} | |
| {"current_steps": 470, "total_steps": 3295, "loss": 0.503, "lr": 9.945870403083164e-06, "epoch": 0.14264577563640501, "percentage": 14.26, "elapsed_time": "3:12:00", "remaining_time": "19:14:05"} | |
| {"current_steps": 480, "total_steps": 3295, "loss": 0.5044, "lr": 9.937818575391654e-06, "epoch": 0.14568079213930726, "percentage": 14.57, "elapsed_time": "3:14:50", "remaining_time": "19:02:41"} | |
| {"current_steps": 490, "total_steps": 3295, "loss": 0.505, "lr": 9.929212401064616e-06, "epoch": 0.14871580864220948, "percentage": 14.87, "elapsed_time": "3:17:58", "remaining_time": "18:53:20"} | |
| {"current_steps": 500, "total_steps": 3295, "loss": 0.4991, "lr": 9.920052846278455e-06, "epoch": 0.15175082514511173, "percentage": 15.17, "elapsed_time": "3:20:33", "remaining_time": "18:41:05"} | |
| {"current_steps": 510, "total_steps": 3295, "loss": 0.4889, "lr": 9.910340939335098e-06, "epoch": 0.15478584164801396, "percentage": 15.48, "elapsed_time": "3:23:50", "remaining_time": "18:33:06"} | |
| {"current_steps": 520, "total_steps": 3295, "loss": 0.488, "lr": 9.900077770546567e-06, "epoch": 0.1578208581509162, "percentage": 15.78, "elapsed_time": "3:26:54", "remaining_time": "18:24:12"} | |
| {"current_steps": 530, "total_steps": 3295, "loss": 0.5025, "lr": 9.889264492112563e-06, "epoch": 0.16085587465381843, "percentage": 16.08, "elapsed_time": "3:29:44", "remaining_time": "18:14:12"} | |
| {"current_steps": 540, "total_steps": 3295, "loss": 0.4946, "lr": 9.877902317991116e-06, "epoch": 0.16389089115672067, "percentage": 16.39, "elapsed_time": "3:33:00", "remaining_time": "18:06:42"} | |
| {"current_steps": 550, "total_steps": 3295, "loss": 0.4989, "lr": 9.865992523762306e-06, "epoch": 0.1669259076596229, "percentage": 16.69, "elapsed_time": "3:35:39", "remaining_time": "17:56:17"} | |
| {"current_steps": 560, "total_steps": 3295, "loss": 0.503, "lr": 9.853536446485048e-06, "epoch": 0.16996092416252515, "percentage": 17.0, "elapsed_time": "3:38:52", "remaining_time": "17:48:57"} | |
| {"current_steps": 570, "total_steps": 3295, "loss": 0.4903, "lr": 9.840535484546996e-06, "epoch": 0.17299594066542737, "percentage": 17.3, "elapsed_time": "3:41:51", "remaining_time": "17:40:40"} | |
| {"current_steps": 580, "total_steps": 3295, "loss": 0.4958, "lr": 9.826991097507548e-06, "epoch": 0.17603095716832962, "percentage": 17.6, "elapsed_time": "3:44:40", "remaining_time": "17:31:42"} | |
| {"current_steps": 590, "total_steps": 3295, "loss": 0.4922, "lr": 9.812904805933989e-06, "epoch": 0.17906597367123184, "percentage": 17.91, "elapsed_time": "3:47:52", "remaining_time": "17:24:43"} | |
| {"current_steps": 600, "total_steps": 3295, "loss": 0.5004, "lr": 9.798278191230783e-06, "epoch": 0.18210099017413406, "percentage": 18.21, "elapsed_time": "3:50:32", "remaining_time": "17:15:30"} | |
| {"current_steps": 610, "total_steps": 3295, "loss": 0.4802, "lr": 9.78311289546204e-06, "epoch": 0.1851360066770363, "percentage": 18.51, "elapsed_time": "3:53:51", "remaining_time": "17:09:20"} | |
| {"current_steps": 620, "total_steps": 3295, "loss": 0.4945, "lr": 9.76741062116716e-06, "epoch": 0.18817102317993853, "percentage": 18.82, "elapsed_time": "3:56:52", "remaining_time": "17:02:00"} | |
| {"current_steps": 630, "total_steps": 3295, "loss": 0.4906, "lr": 9.751173131169705e-06, "epoch": 0.19120603968284078, "percentage": 19.12, "elapsed_time": "3:59:45", "remaining_time": "16:54:11"} | |
| {"current_steps": 640, "total_steps": 3295, "loss": 0.496, "lr": 9.73440224837949e-06, "epoch": 0.194241056185743, "percentage": 19.42, "elapsed_time": "4:03:03", "remaining_time": "16:48:17"} | |
| {"current_steps": 650, "total_steps": 3295, "loss": 0.486, "lr": 9.717099855587935e-06, "epoch": 0.19727607268864525, "percentage": 19.73, "elapsed_time": "4:05:43", "remaining_time": "16:39:55"} | |
| {"current_steps": 660, "total_steps": 3295, "loss": 0.4769, "lr": 9.699267895256695e-06, "epoch": 0.20031108919154747, "percentage": 20.03, "elapsed_time": "4:09:07", "remaining_time": "16:34:36"} | |
| {"current_steps": 670, "total_steps": 3295, "loss": 0.4918, "lr": 9.68090836929958e-06, "epoch": 0.20334610569444972, "percentage": 20.33, "elapsed_time": "4:12:10", "remaining_time": "16:27:58"} | |
| {"current_steps": 680, "total_steps": 3295, "loss": 0.485, "lr": 9.662023338857822e-06, "epoch": 0.20638112219735194, "percentage": 20.64, "elapsed_time": "4:14:56", "remaining_time": "16:20:23"} | |
| {"current_steps": 690, "total_steps": 3295, "loss": 0.4902, "lr": 9.642614924068667e-06, "epoch": 0.2094161387002542, "percentage": 20.94, "elapsed_time": "4:18:07", "remaining_time": "16:14:29"} | |
| {"current_steps": 700, "total_steps": 3295, "loss": 0.4881, "lr": 9.622685303827366e-06, "epoch": 0.2124511552031564, "percentage": 21.24, "elapsed_time": "4:20:41", "remaining_time": "16:06:24"} | |
| {"current_steps": 710, "total_steps": 3295, "loss": 0.4848, "lr": 9.602236715542557e-06, "epoch": 0.21548617170605866, "percentage": 21.55, "elapsed_time": "4:23:57", "remaining_time": "16:01:03"} | |
| {"current_steps": 720, "total_steps": 3295, "loss": 0.4903, "lr": 9.581271454885077e-06, "epoch": 0.21852118820896088, "percentage": 21.85, "elapsed_time": "4:27:01", "remaining_time": "15:54:57"} | |
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