Instructions to use djuna/L3.1-Promissum_Mane-8B-Della-1.5-calc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use djuna/L3.1-Promissum_Mane-8B-Della-1.5-calc with Transformers:

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

pipe = pipeline("text-generation", model="djuna/L3.1-Promissum_Mane-8B-Della-1.5-calc")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("djuna/L3.1-Promissum_Mane-8B-Della-1.5-calc")
model = AutoModelForCausalLM.from_pretrained("djuna/L3.1-Promissum_Mane-8B-Della-1.5-calc", 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 djuna/L3.1-Promissum_Mane-8B-Della-1.5-calc with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "djuna/L3.1-Promissum_Mane-8B-Della-1.5-calc"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "djuna/L3.1-Promissum_Mane-8B-Della-1.5-calc",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/djuna/L3.1-Promissum_Mane-8B-Della-1.5-calc

SGLang

How to use djuna/L3.1-Promissum_Mane-8B-Della-1.5-calc 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 "djuna/L3.1-Promissum_Mane-8B-Della-1.5-calc" \
    --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": "djuna/L3.1-Promissum_Mane-8B-Della-1.5-calc",
		"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 "djuna/L3.1-Promissum_Mane-8B-Della-1.5-calc" \
        --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": "djuna/L3.1-Promissum_Mane-8B-Della-1.5-calc",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use djuna/L3.1-Promissum_Mane-8B-Della-1.5-calc with Docker Model Runner:
```
docker model run hf.co/djuna/L3.1-Promissum_Mane-8B-Della-1.5-calc
```

djuna commited on Oct 29, 2024

Commit

67dc71c

verified ·

1 Parent(s): b0a09aa

Chat Template and EOS

Browse files

Files changed (3) hide show

config.json +5 -1
special_tokens_map.json +1 -1
tokenizer_config.json +4 -2

config.json CHANGED Viewed

@@ -6,7 +6,11 @@
   "attention_bias": false,
   "attention_dropout": 0.0,
   "bos_token_id": 128000,
-  "eos_token_id": 128001,
   "head_dim": 128,
   "hidden_act": "silu",
   "hidden_size": 4096,

   "attention_bias": false,
   "attention_dropout": 0.0,
   "bos_token_id": 128000,
+  "eos_token_id": [
+    128001,
+    128008,
+    128009
+  ],
   "head_dim": 128,
   "hidden_act": "silu",
   "hidden_size": 4096,

special_tokens_map.json CHANGED Viewed

@@ -7,7 +7,7 @@
     "single_word": false
   },
   "eos_token": {
-    "content": "<|end_of_text|>",
     "lstrip": false,
     "normalized": false,
     "rstrip": false,

     "single_word": false
   },
   "eos_token": {
+    "content": "<|eot_id|>",
     "lstrip": false,
     "normalized": false,
     "rstrip": false,

tokenizer_config.json CHANGED Viewed

@@ -2050,14 +2050,16 @@
     }
   },
   "bos_token": "<|begin_of_text|>",
   "clean_up_tokenization_spaces": true,
-  "eos_token": "<|end_of_text|>",
   "model_input_names": [
     "input_ids",
     "attention_mask"
   ],
   "model_max_length": 131072,
-  "pad_token": "<|finetune_right_pad_id|>",
   "padding_side": "left",
   "tokenizer_class": "PreTrainedTokenizerFast"
 }

     }
   },
   "bos_token": "<|begin_of_text|>",
+  "chat_template": "{{ '<|begin_of_text|>' }}{% if messages[0]['role'] == 'system' %}{% set system_message = messages[0]['content'] %}{% endif %}{% if system_message is defined %}{{ '<|start_header_id|>system<|end_header_id|>\n\n' + system_message + '<|eot_id|>' }}{% endif %}{% for message in messages %}{% set content = message['content'] %}{% if message['role'] == 'user' %}{{ '<|start_header_id|>user<|end_header_id|>\n\n' + content + '<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n' }}{% elif message['role'] == 'assistant' %}{{ content + '<|eot_id|>' }}{% endif %}{% endfor %}",
   "clean_up_tokenization_spaces": true,
+  "eos_token": "<|eot_id|>",
   "model_input_names": [
     "input_ids",
     "attention_mask"
   ],
   "model_max_length": 131072,
+  "pad_token": "<|eot_id|>",
   "padding_side": "left",
+  "split_special_tokens": false,
   "tokenizer_class": "PreTrainedTokenizerFast"
 }