Instructions to use esha111/id2223_lab2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use esha111/id2223_lab2 with Transformers:

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

pipe = pipeline("text-generation", model="esha111/id2223_lab2")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("esha111/id2223_lab2")
model = AutoModelForCausalLM.from_pretrained("esha111/id2223_lab2")
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

vLLM

How to use esha111/id2223_lab2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "esha111/id2223_lab2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "esha111/id2223_lab2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/esha111/id2223_lab2

SGLang

How to use esha111/id2223_lab2 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 "esha111/id2223_lab2" \
    --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": "esha111/id2223_lab2",
		"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 "esha111/id2223_lab2" \
        --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": "esha111/id2223_lab2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Studio new

How to use esha111/id2223_lab2 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 esha111/id2223_lab2 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 esha111/id2223_lab2 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for esha111/id2223_lab2 to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="esha111/id2223_lab2",
    max_seq_length=2048,
)

Docker Model Runner
How to use esha111/id2223_lab2 with Docker Model Runner:
```
docker model run hf.co/esha111/id2223_lab2
```

esha111 commited on Dec 7, 2024

Commit

af13fa2

verified ·

1 Parent(s): 3a8efb5

Trained with Unsloth

Browse files

Upload model trained with Unsloth 2x faster

Files changed (3) hide show

config.json +7 -7
generation_config.json +1 -1
model.safetensors +2 -2

config.json CHANGED Viewed

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "unsloth/llama-3.2-3b-instruct-bnb-4bit",
   "architectures": [
     "LlamaForCausalLM"
   ],
@@ -11,16 +11,16 @@
     128008,
     128009
   ],
-  "head_dim": 128,
   "hidden_act": "silu",
-  "hidden_size": 3072,
   "initializer_range": 0.02,
   "intermediate_size": 8192,
   "max_position_embeddings": 131072,
   "mlp_bias": false,
   "model_type": "llama",
-  "num_attention_heads": 24,
-  "num_hidden_layers": 28,
   "num_key_value_heads": 8,
   "pad_token_id": 128004,
   "pretraining_tp": 1,
@@ -47,8 +47,8 @@
   "rope_theta": 500000.0,
   "tie_word_embeddings": true,
   "torch_dtype": "float16",
-  "transformers_version": "4.46.2",
-  "unsloth_version": "2024.11.10",
   "use_cache": true,
   "vocab_size": 128256
 }

 {
+  "_name_or_path": "unsloth/llama-3.2-1b-instruct-bnb-4bit",
   "architectures": [
     "LlamaForCausalLM"
   ],
     128008,
     128009
   ],
+  "head_dim": 64,
   "hidden_act": "silu",
+  "hidden_size": 2048,
   "initializer_range": 0.02,
   "intermediate_size": 8192,
   "max_position_embeddings": 131072,
   "mlp_bias": false,
   "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 16,
   "num_key_value_heads": 8,
   "pad_token_id": 128004,
   "pretraining_tp": 1,
   "rope_theta": 500000.0,
   "tie_word_embeddings": true,
   "torch_dtype": "float16",
+  "transformers_version": "4.46.3",
+  "unsloth_version": "2024.12.4",
   "use_cache": true,
   "vocab_size": 128256
 }

generation_config.json CHANGED Viewed

@@ -10,5 +10,5 @@
   "pad_token_id": 128004,
   "temperature": 0.6,
   "top_p": 0.9,
-  "transformers_version": "4.46.2"
 }

   "pad_token_id": 128004,
   "temperature": 0.6,
   "top_p": 0.9,
+  "transformers_version": "4.46.3"
 }

model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:88aa4d5ee4030668d76ee2036f4195ef6627bdb21e11aeecb3abd0f99542e0fa
-size 2242762539

 version https://git-lfs.github.com/spec/v1
+oid sha256:45247244b0e96858342733d31ea2a441443222d804b6e3b34b9efb96b9330030
+size 1027676590