Instructions to use TildeAI/TildeOpen-30b-64k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TildeAI/TildeOpen-30b-64k with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="TildeAI/TildeOpen-30b-64k", trust_remote_code=True)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("TildeAI/TildeOpen-30b-64k", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("TildeAI/TildeOpen-30b-64k", trust_remote_code=True)

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use TildeAI/TildeOpen-30b-64k with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "TildeAI/TildeOpen-30b-64k"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TildeAI/TildeOpen-30b-64k",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/TildeAI/TildeOpen-30b-64k

SGLang

How to use TildeAI/TildeOpen-30b-64k 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 "TildeAI/TildeOpen-30b-64k" \
    --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": "TildeAI/TildeOpen-30b-64k",
		"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 "TildeAI/TildeOpen-30b-64k" \
        --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": "TildeAI/TildeOpen-30b-64k",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use TildeAI/TildeOpen-30b-64k with Docker Model Runner:
```
docker model run hf.co/TildeAI/TildeOpen-30b-64k
```

Martins Kronis commited on Apr 17

Commit

0a98506

1 Parent(s): 40384dc

Add tokenizer files with LFS

Browse files

Files changed (3) hide show

.gitattributes +1 -0
tokenizer.json +3 -0
tokenizer_config.json +11 -0

.gitattributes CHANGED Viewed

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text

 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

tokenizer.json ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:6d4fc33b73825ee1ce47a3e2b20806c5d5e66318e655ba721885b46359d0bd98
+size 17637164

tokenizer_config.json ADDED Viewed

	@@ -0,0 +1,11 @@

+{
+  "backend": "tokenizers",
+  "bos_token": "<|endoftext|>",
+  "eos_token": "<|endoftext|>",
+  "pad_token": "<|endoftext|>",
+  "padding_side": "left",
+  "model_max_length": 65536,
+  "tokenizer_class": "PreTrainedTokenizerFast",
+  "additional_special_tokens": [],
+  "add_generation_prompt": true
+}