Text Generation
Transformers
Safetensors
English
modern_llm
custom-architecture
rope
gqa
swiglu
rmsnorm
custom_code
Instructions to use devoppro/FastLLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devoppro/FastLLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="devoppro/FastLLM", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("devoppro/FastLLM", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use devoppro/FastLLM with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "devoppro/FastLLM" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "devoppro/FastLLM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/devoppro/FastLLM
- SGLang
How to use devoppro/FastLLM 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 "devoppro/FastLLM" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "devoppro/FastLLM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "devoppro/FastLLM" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "devoppro/FastLLM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use devoppro/FastLLM with Docker Model Runner:
docker model run hf.co/devoppro/FastLLM
Training in progress, step 1200, checkpoint
Browse files
last-checkpoint/model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1235573136
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:68d10d6c77661a22b49f687a60f7c0595cbbc5bdafd8820a654f5e22542b0e33
|
| 3 |
size 1235573136
|
last-checkpoint/optimizer.pt
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 2471218763
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:34eb8fd94484f12828f3079ddb1062719a88baf43040ad9bfe0255470c6e514a
|
| 3 |
size 2471218763
|
last-checkpoint/scaler.pt
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1383
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:526edfc17cc77c8e1a37fdb81a9a703de4513b58ba4b0dbf11906a54aab78396
|
| 3 |
size 1383
|
last-checkpoint/scheduler.pt
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1465
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c692682bd43a00387bd41dcd12b266427cdc8a4657c91543547ea08ad6b10378
|
| 3 |
size 1465
|
last-checkpoint/trainer_state.json
CHANGED
|
@@ -2,9 +2,9 @@
|
|
| 2 |
"best_global_step": null,
|
| 3 |
"best_metric": null,
|
| 4 |
"best_model_checkpoint": null,
|
| 5 |
-
"epoch": 0.
|
| 6 |
"eval_steps": 500,
|
| 7 |
-
"global_step":
|
| 8 |
"is_hyper_param_search": false,
|
| 9 |
"is_local_process_zero": true,
|
| 10 |
"is_world_process_zero": true,
|
|
@@ -778,6 +778,76 @@
|
|
| 778 |
"learning_rate": 0.00029399398797595185,
|
| 779 |
"loss": 68.12153930664063,
|
| 780 |
"step": 1100
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 781 |
}
|
| 782 |
],
|
| 783 |
"logging_steps": 10,
|
|
@@ -797,7 +867,7 @@
|
|
| 797 |
"attributes": {}
|
| 798 |
}
|
| 799 |
},
|
| 800 |
-
"total_flos": 1.
|
| 801 |
"train_batch_size": 2,
|
| 802 |
"trial_name": null,
|
| 803 |
"trial_params": null
|
|
|
|
| 2 |
"best_global_step": null,
|
| 3 |
"best_metric": null,
|
| 4 |
"best_model_checkpoint": null,
|
| 5 |
+
"epoch": 0.024,
|
| 6 |
"eval_steps": 500,
|
| 7 |
+
"global_step": 1200,
|
| 8 |
"is_hyper_param_search": false,
|
| 9 |
"is_local_process_zero": true,
|
| 10 |
"is_world_process_zero": true,
|
|
|
|
| 778 |
"learning_rate": 0.00029399398797595185,
|
| 779 |
"loss": 68.12153930664063,
|
| 780 |
"step": 1100
|
| 781 |
+
},
|
| 782 |
+
{
|
| 783 |
+
"epoch": 0.0222,
|
| 784 |
+
"grad_norm": 9.84087085723877,
|
| 785 |
+
"learning_rate": 0.0002939338677354709,
|
| 786 |
+
"loss": 73.03311767578126,
|
| 787 |
+
"step": 1110
|
| 788 |
+
},
|
| 789 |
+
{
|
| 790 |
+
"epoch": 0.0224,
|
| 791 |
+
"grad_norm": 8.5576171875,
|
| 792 |
+
"learning_rate": 0.00029387374749498995,
|
| 793 |
+
"loss": 67.728662109375,
|
| 794 |
+
"step": 1120
|
| 795 |
+
},
|
| 796 |
+
{
|
| 797 |
+
"epoch": 0.0226,
|
| 798 |
+
"grad_norm": 6.275845050811768,
|
| 799 |
+
"learning_rate": 0.000293813627254509,
|
| 800 |
+
"loss": 59.14338989257813,
|
| 801 |
+
"step": 1130
|
| 802 |
+
},
|
| 803 |
+
{
|
| 804 |
+
"epoch": 0.0228,
|
| 805 |
+
"grad_norm": 10.62365436553955,
|
| 806 |
+
"learning_rate": 0.00029375350701402804,
|
| 807 |
+
"loss": 68.015625,
|
| 808 |
+
"step": 1140
|
| 809 |
+
},
|
| 810 |
+
{
|
| 811 |
+
"epoch": 0.023,
|
| 812 |
+
"grad_norm": 10.124994277954102,
|
| 813 |
+
"learning_rate": 0.0002936933867735471,
|
| 814 |
+
"loss": 67.996630859375,
|
| 815 |
+
"step": 1150
|
| 816 |
+
},
|
| 817 |
+
{
|
| 818 |
+
"epoch": 0.0232,
|
| 819 |
+
"grad_norm": 9.192570686340332,
|
| 820 |
+
"learning_rate": 0.00029363326653306614,
|
| 821 |
+
"loss": 69.9107177734375,
|
| 822 |
+
"step": 1160
|
| 823 |
+
},
|
| 824 |
+
{
|
| 825 |
+
"epoch": 0.0234,
|
| 826 |
+
"grad_norm": 11.012198448181152,
|
| 827 |
+
"learning_rate": 0.00029357314629258513,
|
| 828 |
+
"loss": 72.0302978515625,
|
| 829 |
+
"step": 1170
|
| 830 |
+
},
|
| 831 |
+
{
|
| 832 |
+
"epoch": 0.0236,
|
| 833 |
+
"grad_norm": 8.58188533782959,
|
| 834 |
+
"learning_rate": 0.0002935130260521042,
|
| 835 |
+
"loss": 73.009423828125,
|
| 836 |
+
"step": 1180
|
| 837 |
+
},
|
| 838 |
+
{
|
| 839 |
+
"epoch": 0.0238,
|
| 840 |
+
"grad_norm": 11.214829444885254,
|
| 841 |
+
"learning_rate": 0.0002934529058116232,
|
| 842 |
+
"loss": 69.40020141601562,
|
| 843 |
+
"step": 1190
|
| 844 |
+
},
|
| 845 |
+
{
|
| 846 |
+
"epoch": 0.024,
|
| 847 |
+
"grad_norm": 8.615409851074219,
|
| 848 |
+
"learning_rate": 0.0002933927855711423,
|
| 849 |
+
"loss": 73.381103515625,
|
| 850 |
+
"step": 1200
|
| 851 |
}
|
| 852 |
],
|
| 853 |
"logging_steps": 10,
|
|
|
|
| 867 |
"attributes": {}
|
| 868 |
}
|
| 869 |
},
|
| 870 |
+
"total_flos": 1.253963749312512e+16,
|
| 871 |
"train_batch_size": 2,
|
| 872 |
"trial_name": null,
|
| 873 |
"trial_params": null
|