Instructions to use rahulvk007/ExtractQueNumberMini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use rahulvk007/ExtractQueNumberMini with Transformers:

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

pipe = pipeline("text-generation", model="rahulvk007/ExtractQueNumberMini")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("rahulvk007/ExtractQueNumberMini")
model = AutoModelForCausalLM.from_pretrained("rahulvk007/ExtractQueNumberMini")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use rahulvk007/ExtractQueNumberMini with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "rahulvk007/ExtractQueNumberMini"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "rahulvk007/ExtractQueNumberMini",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/rahulvk007/ExtractQueNumberMini

SGLang

How to use rahulvk007/ExtractQueNumberMini 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 "rahulvk007/ExtractQueNumberMini" \
    --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": "rahulvk007/ExtractQueNumberMini",
		"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 "rahulvk007/ExtractQueNumberMini" \
        --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": "rahulvk007/ExtractQueNumberMini",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Unsloth Studio new

How to use rahulvk007/ExtractQueNumberMini 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 rahulvk007/ExtractQueNumberMini 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 rahulvk007/ExtractQueNumberMini to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for rahulvk007/ExtractQueNumberMini to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="rahulvk007/ExtractQueNumberMini",
    max_seq_length=2048,
)

Docker Model Runner
How to use rahulvk007/ExtractQueNumberMini with Docker Model Runner:
```
docker model run hf.co/rahulvk007/ExtractQueNumberMini
```

rahulvk007 commited on Nov 1, 2024

Commit

9a0aeee

verified ·

1 Parent(s): 2b0f5b7

Trained with Unsloth

Browse files

Files changed (4) hide show

README.md +1 -0
config.json +34 -0
generation_config.json +8 -0
pytorch_model.bin +3 -0

README.md CHANGED Viewed

@@ -9,6 +9,7 @@ tags:
 - unsloth
 - llama
 - trl
 ---
 # Uploaded  model

 - unsloth
 - llama
 - trl
+- sft
 ---
 # Uploaded  model

config.json ADDED Viewed

	@@ -0,0 +1,34 @@

+{
+  "_name_or_path": "unsloth/SmolLM2-135M",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 0,
+  "eos_token_id": 0,
+  "head_dim": 64,
+  "hidden_act": "silu",
+  "hidden_size": 576,
+  "initializer_range": 0.041666666666666664,
+  "intermediate_size": 1536,
+  "is_llama_config": true,
+  "max_position_embeddings": 8192,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 9,
+  "num_hidden_layers": 30,
+  "num_key_value_heads": 3,
+  "pad_token_id": 49152,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_interleaved": false,
+  "rope_scaling": null,
+  "rope_theta": 100000,
+  "tie_word_embeddings": true,
+  "torch_dtype": "float16",
+  "transformers_version": "4.46.1",
+  "unsloth_version": "2024.10.7",
+  "use_cache": true,
+  "vocab_size": 49153
+}

generation_config.json ADDED Viewed

	@@ -0,0 +1,8 @@

+{
+  "_from_model_config": true,
+  "bos_token_id": 0,
+  "eos_token_id": 0,
+  "max_length": 8192,
+  "pad_token_id": 49152,
+  "transformers_version": "4.46.1"
+}

pytorch_model.bin ADDED Viewed

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

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+oid sha256:3907b49f886f3dc242cc9705ecb362eb32464d3668c2978616f0007333604246
+size 269123146