Instructions to use SlayerLab/pollock-mini-lm-125m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use SlayerLab/pollock-mini-lm-125m with Transformers:

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

pipe = pipeline("text-generation", model="SlayerLab/pollock-mini-lm-125m", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("SlayerLab/pollock-mini-lm-125m", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use SlayerLab/pollock-mini-lm-125m with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "SlayerLab/pollock-mini-lm-125m"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "SlayerLab/pollock-mini-lm-125m",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/SlayerLab/pollock-mini-lm-125m

SGLang

How to use SlayerLab/pollock-mini-lm-125m 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 "SlayerLab/pollock-mini-lm-125m" \
    --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": "SlayerLab/pollock-mini-lm-125m",
		"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 "SlayerLab/pollock-mini-lm-125m" \
        --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": "SlayerLab/pollock-mini-lm-125m",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use SlayerLab/pollock-mini-lm-125m with Docker Model Runner:
```
docker model run hf.co/SlayerLab/pollock-mini-lm-125m
```

Release Pollock 1.5 (r007)

by dawidmajewski - opened 14 days ago

base: refs/heads/main

←

from: refs/pr/3

Discussion Files changed

+36091

-35344

Add Pollock 1.5 core artifactsf2a1ec07

dawidmajewski

Fabryka AI org 14 days ago

Stage the verified r007 E4-best weights, model configuration, and tokenizer before replaying fixed inference from this immutable commit.

Complete Pollock 1.5 release candidatef249f5fd

dawidmajewski

Fabryka AI org 14 days ago

Release candidate complete. Core weights are pinned at commit f2a1ec072098d257c36b129b0e554e2e6de9c46e (model.safetensors SHA-256 4a88432225dac6255ae1e2a085019f36dcdaf55fa33c77629dba6e7445c6c2fb). The final PR commit f249f5fd82b415eb1cd4e79ac051ef029a9583ab includes the E4-best benchmark, exact immutable fixed-inference replay, model card, histories, and release manifest. All 25 manifest artifact hashes were verified from the remote PR commit.

dawidmajewski changed pull request title from Add Pollock 1.5 core artifacts to Release Pollock 1.5 (r007) 14 days ago

dawidmajewski

Fabryka AI org 14 days ago

Verified release candidate: immutable weights replay passed and all 25 manifest artifact hashes matched the remote PR commit.

dawidmajewski changed pull request status to merged 14 days ago

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