Instructions to use katuni4ka/tiny-random-falcon-40b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use katuni4ka/tiny-random-falcon-40b with Transformers:

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

pipe = pipeline("text-generation", model="katuni4ka/tiny-random-falcon-40b")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("katuni4ka/tiny-random-falcon-40b")
model = AutoModelForCausalLM.from_pretrained("katuni4ka/tiny-random-falcon-40b")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use katuni4ka/tiny-random-falcon-40b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "katuni4ka/tiny-random-falcon-40b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "katuni4ka/tiny-random-falcon-40b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/katuni4ka/tiny-random-falcon-40b

SGLang

How to use katuni4ka/tiny-random-falcon-40b 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 "katuni4ka/tiny-random-falcon-40b" \
    --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": "katuni4ka/tiny-random-falcon-40b",
		"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 "katuni4ka/tiny-random-falcon-40b" \
        --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": "katuni4ka/tiny-random-falcon-40b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use katuni4ka/tiny-random-falcon-40b with Docker Model Runner:
```
docker model run hf.co/katuni4ka/tiny-random-falcon-40b
```

katuni4ka commited on Jul 2, 2024

Commit

f4dd2e8

verified ·

1 Parent(s): 566462a

Update config.json

Browse files

Files changed (1) hide show

config.json +0 -8

config.json CHANGED Viewed

@@ -6,14 +6,6 @@
     "FalconForCausalLM"
   ],
   "attention_dropout": 0.0,
-  "auto_map": {
-    "AutoConfig": "configuration_falcon.FalconConfig",
-    "AutoModel": "modeling_falcon.FalconModel",
-    "AutoModelForCausalLM": "modeling_falcon.FalconForCausalLM",
-    "AutoModelForQuestionAnswering": "modeling_falcon.FalconForQuestionAnswering",
-    "AutoModelForSequenceClassification": "modeling_falcon.FalconForSequenceClassification",
-    "AutoModelForTokenClassification": "modeling_falcon.FalconForTokenClassification"
-  },
   "bias": false,
   "bos_token_id": 11,
   "eos_token_id": 11,

     "FalconForCausalLM"
   ],
   "attention_dropout": 0.0,
   "bias": false,
   "bos_token_id": 11,
   "eos_token_id": 11,