Instructions to use twright8/phim_q16_vllm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use twright8/phim_q16_vllm with Transformers:

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

pipe = pipeline("text-generation", model="twright8/phim_q16_vllm")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("twright8/phim_q16_vllm")
model = AutoModelForCausalLM.from_pretrained("twright8/phim_q16_vllm", 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 twright8/phim_q16_vllm with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "twright8/phim_q16_vllm"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "twright8/phim_q16_vllm",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/twright8/phim_q16_vllm

SGLang

How to use twright8/phim_q16_vllm 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 "twright8/phim_q16_vllm" \
    --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": "twright8/phim_q16_vllm",
		"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 "twright8/phim_q16_vllm" \
        --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": "twright8/phim_q16_vllm",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Studio

How to use twright8/phim_q16_vllm 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 twright8/phim_q16_vllm 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 twright8/phim_q16_vllm to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for twright8/phim_q16_vllm to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="twright8/phim_q16_vllm",
    max_seq_length=2048,
)

Docker Model Runner
How to use twright8/phim_q16_vllm with Docker Model Runner:
```
docker model run hf.co/twright8/phim_q16_vllm
```

twright8 commited on Aug 7, 2024

Commit

626d8c5

verified ·

1 Parent(s): 9b37825

Upload tokenizer

Browse files

Files changed (3) hide show

special_tokens_map.json +1 -1
tokenizer.json +1 -1
tokenizer_config.json +3 -3

special_tokens_map.json CHANGED Viewed

@@ -17,7 +17,7 @@
     "content": "<|placeholder6|>",
     "lstrip": false,
     "normalized": false,
-    "rstrip": true,
     "single_word": false
   },
   "unk_token": {

     "content": "<|placeholder6|>",
     "lstrip": false,
     "normalized": false,
+    "rstrip": false,
     "single_word": false
   },
   "unk_token": {

tokenizer.json CHANGED Viewed

@@ -116,7 +116,7 @@
       "content": "<|placeholder6|>",
       "single_word": false,
       "lstrip": false,
-      "rstrip": true,
       "normalized": false,
       "special": true
     },

       "content": "<|placeholder6|>",
       "single_word": false,
       "lstrip": false,
+      "rstrip": false,
       "normalized": false,
       "special": true
     },

tokenizer_config.json CHANGED Viewed

@@ -103,7 +103,7 @@
       "content": "<|placeholder6|>",
       "lstrip": false,
       "normalized": false,
-      "rstrip": true,
       "single_word": false,
       "special": true
     },
@@ -117,10 +117,10 @@
     }
   },
   "bos_token": "<s>",
-  "chat_template": "{% for message in messages %}{% if (message['role'] == 'user') %}{{'<|user|>' + '\n' + message['content'] + '<|end|>' + '\n' + '<|assistant|>' + '\n'}}{% elif (message['role'] == 'assistant') %}{{message['content'] + '<|end|>' + '\n'}}{% endif %}{% endfor %}",
   "clean_up_tokenization_spaces": false,
   "eos_token": "<|endoftext|>",
-  "legacy": true,
   "model_max_length": 4096,
   "pad_token": "<|placeholder6|>",
   "padding_side": "left",

       "content": "<|placeholder6|>",
       "lstrip": false,
       "normalized": false,
+      "rstrip": false,
       "single_word": false,
       "special": true
     },
     }
   },
   "bos_token": "<s>",
+  "chat_template": "{% for message in messages %}{% if message['role'] == 'user' %}{{'<|user|>\n' + message['content'] + '<|end|>\n'}}{% elif message['role'] == 'assistant' %}{{'<|assistant|>\n' + message['content'] + '<|end|>\n'}}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|assistant|>\n' }}{% else %}{{ eos_token }}{% endif %}",
   "clean_up_tokenization_spaces": false,
   "eos_token": "<|endoftext|>",
+  "legacy": false,
   "model_max_length": 4096,
   "pad_token": "<|placeholder6|>",
   "padding_side": "left",