Text Generation
Transformers
TensorBoard
Safetensors
opt
Generated from Trainer
text-generation-inference
Instructions to use ccore/getcode with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ccore/getcode with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ccore/getcode")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ccore/getcode") model = AutoModelForCausalLM.from_pretrained("ccore/getcode") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ccore/getcode with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ccore/getcode" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ccore/getcode", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ccore/getcode
- SGLang
How to use ccore/getcode 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 "ccore/getcode" \ --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": "ccore/getcode", "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 "ccore/getcode" \ --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": "ccore/getcode", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ccore/getcode with Docker Model Runner:
docker model run hf.co/ccore/getcode
Training in progress, epoch 1
Browse files- model.safetensors +1 -1
- runs/Feb11_01-30-56_0c9763e1c3ff/events.out.tfevents.1739237456.0c9763e1c3ff.31.0 +3 -0
- runs/Feb11_01-33-17_0c9763e1c3ff/events.out.tfevents.1739237598.0c9763e1c3ff.124.0 +3 -0
- runs/Feb11_01-40-11_0c9763e1c3ff/events.out.tfevents.1739238012.0c9763e1c3ff.196.0 +3 -0
- training_args.bin +3 -0
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 500979600
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:1cf838e3ff323c964eb5a4dee4ae78ba71fccae1da29d2c6a9985c8659ec6bb5
|
| 3 |
size 500979600
|
runs/Feb11_01-30-56_0c9763e1c3ff/events.out.tfevents.1739237456.0c9763e1c3ff.31.0
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:e53f5eaa06e82f454a238042079018738645866ae4011dfff97b4e2daed08c72
|
| 3 |
+
size 4184
|
runs/Feb11_01-33-17_0c9763e1c3ff/events.out.tfevents.1739237598.0c9763e1c3ff.124.0
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:a0bccfde6f90132d90260501dc9e6280006a8cdac73213d5085de61374e73bc2
|
| 3 |
+
size 5125
|
runs/Feb11_01-40-11_0c9763e1c3ff/events.out.tfevents.1739238012.0c9763e1c3ff.196.0
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:3e07c6d525f48aeb8c3ebf9ab4285f9e8908a71be7fe0305c15cc88a2eddde2e
|
| 3 |
+
size 5391
|
training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0017a8d69cb5eb07db982774b9507cf45f8391374e94aa47a6813fcd16581db9
|
| 3 |
+
size 5368
|