Instructions to use DominusDeorum/Knowledge-rep_full-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use DominusDeorum/Knowledge-rep_full-model with Transformers:

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

pipe = pipeline("text-generation", model="DominusDeorum/Knowledge-rep_full-model")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("DominusDeorum/Knowledge-rep_full-model")
model = AutoModelForCausalLM.from_pretrained("DominusDeorum/Knowledge-rep_full-model", device_map="auto")
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 Settings

vLLM

How to use DominusDeorum/Knowledge-rep_full-model with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "DominusDeorum/Knowledge-rep_full-model"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "DominusDeorum/Knowledge-rep_full-model",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/DominusDeorum/Knowledge-rep_full-model

SGLang

How to use DominusDeorum/Knowledge-rep_full-model 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 "DominusDeorum/Knowledge-rep_full-model" \
    --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": "DominusDeorum/Knowledge-rep_full-model",
		"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 "DominusDeorum/Knowledge-rep_full-model" \
        --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": "DominusDeorum/Knowledge-rep_full-model",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Studio

How to use DominusDeorum/Knowledge-rep_full-model with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for DominusDeorum/Knowledge-rep_full-model to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for DominusDeorum/Knowledge-rep_full-model to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for DominusDeorum/Knowledge-rep_full-model to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="DominusDeorum/Knowledge-rep_full-model",
    max_seq_length=2048,
)

Docker Model Runner
How to use DominusDeorum/Knowledge-rep_full-model with Docker Model Runner:
```
docker model run hf.co/DominusDeorum/Knowledge-rep_full-model
```

DominusDeorum commited on Nov 23, 2024

Commit

830978b

verified ·

1 Parent(s): a86452d

Upload model trained with Unsloth

Browse files

Upload model trained with Unsloth 2x faster

Files changed (2) hide show

config.json +1 -1
model.safetensors +1 -1

config.json CHANGED Viewed

@@ -48,7 +48,7 @@
   "tie_word_embeddings": true,
   "torch_dtype": "float16",
   "transformers_version": "4.46.2",
-  "unsloth_version": "2024.11.7",
   "use_cache": true,
   "vocab_size": 128256
 }

   "tie_word_embeddings": true,
   "torch_dtype": "float16",
   "transformers_version": "4.46.2",
+  "unsloth_version": "2024.11.9",
   "use_cache": true,
   "vocab_size": 128256
 }

model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:30c1f74b3c9eacead405998472030105ec0ea1a2257d0677f1975b4435d24c63
 size 1072801777

 version https://git-lfs.github.com/spec/v1
+oid sha256:e2546c1512b8a2e42f92ecd8dcee2d0ad43299418f87ed22df20117ef8377b90
 size 1072801777