Instructions to use replit/replit-code-v1-3b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use replit/replit-code-v1-3b with Transformers:

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

pipe = pipeline("text-generation", model="replit/replit-code-v1-3b", trust_remote_code=True)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("replit/replit-code-v1-3b", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("replit/replit-code-v1-3b", trust_remote_code=True)

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use replit/replit-code-v1-3b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "replit/replit-code-v1-3b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "replit/replit-code-v1-3b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/replit/replit-code-v1-3b

SGLang

How to use replit/replit-code-v1-3b 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 "replit/replit-code-v1-3b" \
    --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": "replit/replit-code-v1-3b",
		"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 "replit/replit-code-v1-3b" \
        --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": "replit/replit-code-v1-3b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use replit/replit-code-v1-3b with Docker Model Runner:
```
docker model run hf.co/replit/replit-code-v1-3b
```

Update replit_lm_tokenizer.py

#33

by dobbySeo - opened Apr 17, 2024

base: refs/heads/main

←

from: refs/pr/33

Discussion Files changed

-1

dobbySeo

Apr 17, 2024

When initializing the tokenizer, error occurs that using sp_model before sp_model instance initialization.

Traceback (most recent call last):
  File "/home/dobby/trainer/examples/function_calling/preprocessing.py", line 93, in <module>
    preprocess(bpe_process, args)
  File "/home/dobby/trainer/examples/function_calling/preprocessing.py", line 53, in preprocess
    tokenizer = AutoTokenizer.from_pretrained(
  File "/home/dobby/.cache/pypoetry/virtualenvs/trainer-lQlppuIx-py3.10/lib/python3.10/site-packages/transformers/models/auto/tokenization_auto.py", line 819, in from_pretrained
    return tokenizer_class.from_pretrained(
  File "/home/dobby/.cache/pypoetry/virtualenvs/trainer-lQlppuIx-py3.10/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 2059, in from_pretrained
    return cls._from_pretrained(
  File "/home/dobby/.cache/pypoetry/virtualenvs/trainer-lQlppuIx-py3.10/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 2298, in _from_pretrained
    tokenizer = cls(*init_inputs, **init_kwargs)
  File "/home/dobby/.cache/huggingface/modules/transformers_modules/replit/replit-code-v1-3b/cc0a4f17a8d72b71d62ea53cb0e23e4dac352067/replit_lm_tokenizer.py", line 66, in __init__
    super().__init__(bos_token=bos_token, eos_token=eos_token, unk_token=unk_token, pad_token=pad_token, sep_token=sep_token, sp_model_kwargs=self.sp_model_kwargs, **kwargs)
  File "/home/dobby/.cache/pypoetry/virtualenvs/trainer-lQlppuIx-py3.10/lib/python3.10/site-packages/transformers/tokenization_utils.py", line 367, in __init__
    self._add_tokens(
  File "/home/dobby/.cache/pypoetry/virtualenvs/trainer-lQlppuIx-py3.10/lib/python3.10/site-packages/transformers/tokenization_utils.py", line 467, in _add_tokens
    current_vocab = self.get_vocab().copy()
  File "/home/dobby/.cache/huggingface/modules/transformers_modules/replit/replit-code-v1-3b/cc0a4f17a8d72b71d62ea53cb0e23e4dac352067/replit_lm_tokenizer.py", line 76, in get_vocab
    vocab = {self.convert_ids_to_tokens(i): i for i in range(self.vocab_size)}
  File "/home/dobby/.cache/huggingface/modules/transformers_modules/replit/replit-code-v1-3b/cc0a4f17a8d72b71d62ea53cb0e23e4dac352067/replit_lm_tokenizer.py", line 73, in vocab_size
    return self.sp_model.get_piece_size()
AttributeError: 'ReplitLMTokenizer' object has no attribute 'sp_model'

So I change super class initialization at the last.

Update replit_lm_tokenizer.pyc69cea3e

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

Ready to merge

This branch is ready to get merged automatically.

· Sign up or log in to comment