Instructions to use craa/100M_low_500_6910 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use craa/100M_low_500_6910 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="craa/100M_low_500_6910")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("craa/100M_low_500_6910") model = AutoModelForCausalLM.from_pretrained("craa/100M_low_500_6910") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use craa/100M_low_500_6910 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "craa/100M_low_500_6910" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "craa/100M_low_500_6910", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/craa/100M_low_500_6910
- SGLang
How to use craa/100M_low_500_6910 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 "craa/100M_low_500_6910" \ --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": "craa/100M_low_500_6910", "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 "craa/100M_low_500_6910" \ --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": "craa/100M_low_500_6910", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use craa/100M_low_500_6910 with Docker Model Runner:
docker model run hf.co/craa/100M_low_500_6910
Training in progress, step 90000, checkpoint
Browse files
checkpoint-90000/model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 503128704
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:1baf5415f58e901602bd6841a15caa62a2191755651dcce51969f67800610061
|
| 3 |
size 503128704
|
checkpoint-90000/optimizer.pt
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1006351290
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d0d14feb77c0da826d7e84686301439ce70f0eef8f9da6968127d8c8a32048fb
|
| 3 |
size 1006351290
|
checkpoint-90000/scheduler.pt
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1064
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:6cc0526fec3e82fba03edee49af1d6bd8bf8c692b3cf613fe828924883c0d780
|
| 3 |
size 1064
|
checkpoint-90000/trainer_state.json
CHANGED
|
The diff for this file is too large to render.
See raw diff
|
|
|
checkpoint-90000/training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 5304
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:16762723462bf3f230aa9262ba078e231590e2bc0ce83931aa6546e32c5c8042
|
| 3 |
size 5304
|