Instructions to use Pluto-AI-Labs/Atlas-Frontier-Distill-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Pluto-AI-Labs/Atlas-Frontier-Distill-3B with Transformers:

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

pipe = pipeline("text-generation", model="Pluto-AI-Labs/Atlas-Frontier-Distill-3B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Pluto-AI-Labs/Atlas-Frontier-Distill-3B")
model = AutoModelForCausalLM.from_pretrained("Pluto-AI-Labs/Atlas-Frontier-Distill-3B", 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 Pluto-AI-Labs/Atlas-Frontier-Distill-3B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Pluto-AI-Labs/Atlas-Frontier-Distill-3B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Pluto-AI-Labs/Atlas-Frontier-Distill-3B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Pluto-AI-Labs/Atlas-Frontier-Distill-3B

SGLang

How to use Pluto-AI-Labs/Atlas-Frontier-Distill-3B 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 "Pluto-AI-Labs/Atlas-Frontier-Distill-3B" \
    --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": "Pluto-AI-Labs/Atlas-Frontier-Distill-3B",
		"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 "Pluto-AI-Labs/Atlas-Frontier-Distill-3B" \
        --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": "Pluto-AI-Labs/Atlas-Frontier-Distill-3B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Pluto-AI-Labs/Atlas-Frontier-Distill-3B with Docker Model Runner:
```
docker model run hf.co/Pluto-AI-Labs/Atlas-Frontier-Distill-3B
```

Siddh07ETH commited on 24 days ago

Commit

cf5efba

verified ·

1 Parent(s): 1495964

Upload Qwen2ForCausalLM

Browse files

Files changed (4) hide show

README.md +0 -3
config.json +5 -20
generation_config.json +2 -1
model.safetensors +2 -2

README.md CHANGED Viewed

@@ -2,7 +2,6 @@
 license: apache-2.0
 language:
 - en
 tags:
 - distillation
 - coding
@@ -13,11 +12,9 @@ tags:
 - fable-5
 - frontier-models
 - qlora
 base_model: Qwen/Qwen2.5-Coder-3B-Instruct
 pipeline_tag: text-generation
 library_name: transformers
 datasets:
 - Siddh07ETH/Atlas-Frontier-Model-Traces
 ---

 license: apache-2.0
 language:
 - en
 tags:
 - distillation
 - coding
 - fable-5
 - frontier-models
 - qlora
 base_model: Qwen/Qwen2.5-Coder-3B-Instruct
 pipeline_tag: text-generation
 library_name: transformers
 datasets:
 - Siddh07ETH/Atlas-Frontier-Model-Traces
 ---

config.json CHANGED Viewed

@@ -3,8 +3,8 @@
     "Qwen2ForCausalLM"
   ],
   "attention_dropout": 0.0,
-  "bos_token_id": null,
-  "dtype": "float32",
   "eos_token_id": 151645,
   "hidden_act": "silu",
   "hidden_size": 2048,
@@ -54,22 +54,7 @@
   "num_attention_heads": 16,
   "num_hidden_layers": 36,
   "num_key_value_heads": 2,
-  "pad_token_id": 151643,
-  "quantization_config": {
-    "_load_in_4bit": true,
-    "_load_in_8bit": false,
-    "bnb_4bit_compute_dtype": "float16",
-    "bnb_4bit_quant_storage": "uint8",
-    "bnb_4bit_quant_type": "nf4",
-    "bnb_4bit_use_double_quant": false,
-    "llm_int8_enable_fp32_cpu_offload": false,
-    "llm_int8_has_fp16_weight": false,
-    "llm_int8_skip_modules": null,
-    "llm_int8_threshold": 6.0,
-    "load_in_4bit": true,
-    "load_in_8bit": false,
-    "quant_method": "bitsandbytes"
-  },
   "rms_norm_eps": 1e-06,
   "rope_parameters": {
     "rope_theta": 1000000.0,
@@ -77,8 +62,8 @@
   },
   "sliding_window": null,
   "tie_word_embeddings": true,
-  "transformers_version": "5.14.1",
-  "use_cache": false,
   "use_sliding_window": false,
   "vocab_size": 151936
 }

     "Qwen2ForCausalLM"
   ],
   "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "dtype": "float16",
   "eos_token_id": 151645,
   "hidden_act": "silu",
   "hidden_size": 2048,
   "num_attention_heads": 16,
   "num_hidden_layers": 36,
   "num_key_value_heads": 2,
+  "pad_token_id": null,
   "rms_norm_eps": 1e-06,
   "rope_parameters": {
     "rope_theta": 1000000.0,
   },
   "sliding_window": null,
   "tie_word_embeddings": true,
+  "transformers_version": "5.0.0",
+  "use_cache": true,
   "use_sliding_window": false,
   "vocab_size": 151936
 }

generation_config.json CHANGED Viewed

@@ -1,4 +1,5 @@
 {
   "do_sample": true,
   "eos_token_id": [
     151645,
@@ -9,5 +10,5 @@
   "temperature": 0.7,
   "top_k": 20,
   "top_p": 0.8,
-  "transformers_version": "5.14.1"
 }

 {
+  "bos_token_id": 151643,
   "do_sample": true,
   "eos_token_id": [
     151645,
   "temperature": 0.7,
   "top_k": 20,
   "top_p": 0.8,
+  "transformers_version": "5.0.0"
 }

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