Instructions to use misterJB/naima-dojo-741hz-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use misterJB/naima-dojo-741hz-v3 with Transformers:

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

pipe = pipeline("text-generation", model="misterJB/naima-dojo-741hz-v3")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("misterJB/naima-dojo-741hz-v3")
model = AutoModelForMultimodalLM.from_pretrained("misterJB/naima-dojo-741hz-v3")
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 misterJB/naima-dojo-741hz-v3 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "misterJB/naima-dojo-741hz-v3"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "misterJB/naima-dojo-741hz-v3",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/misterJB/naima-dojo-741hz-v3

SGLang

How to use misterJB/naima-dojo-741hz-v3 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 "misterJB/naima-dojo-741hz-v3" \
    --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": "misterJB/naima-dojo-741hz-v3",
		"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 "misterJB/naima-dojo-741hz-v3" \
        --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": "misterJB/naima-dojo-741hz-v3",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Studio

How to use misterJB/naima-dojo-741hz-v3 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 misterJB/naima-dojo-741hz-v3 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 misterJB/naima-dojo-741hz-v3 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for misterJB/naima-dojo-741hz-v3 to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="misterJB/naima-dojo-741hz-v3",
    max_seq_length=2048,
)

Docker Model Runner
How to use misterJB/naima-dojo-741hz-v3 with Docker Model Runner:
```
docker model run hf.co/misterJB/naima-dojo-741hz-v3
```

misterJB commited on May 9

Commit

7030bb0

verified ·

1 Parent(s): 322c6a0

Upload model trained with Unsloth

Browse files

Upload model trained with Unsloth 2x faster

Files changed (2) hide show

adapter_config.json +2 -2
adapter_model.safetensors +1 -1

adapter_config.json CHANGED Viewed

@@ -34,9 +34,9 @@
   "rank_pattern": {},
   "revision": null,
   "target_modules": [
-    "k_proj",
-    "o_proj",
     "q_proj",
     "v_proj"
   ],
   "target_parameters": null,

   "rank_pattern": {},
   "revision": null,
   "target_modules": [
     "q_proj",
+    "o_proj",
+    "k_proj",
     "v_proj"
   ],
   "target_parameters": null,

adapter_model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:55090dd49eb26d79cd42199b29bb3d04ae40b74ecbc3eca6d201575d66d10463
 size 31876192

 version https://git-lfs.github.com/spec/v1
+oid sha256:c5c795c5c6201c74897e217d267e5c08d49a29402fc95ff42cff0088696de173
 size 31876192