databricks/databricks-dolly-15k
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How to use rustformers/dolly-v2-ggml with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-generation", model="rustformers/dolly-v2-ggml") # Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("rustformers/dolly-v2-ggml", dtype="auto")How to use rustformers/dolly-v2-ggml with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "rustformers/dolly-v2-ggml"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "rustformers/dolly-v2-ggml",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'docker model run hf.co/rustformers/dolly-v2-ggml
How to use rustformers/dolly-v2-ggml with SGLang:
# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
--model-path "rustformers/dolly-v2-ggml" \
--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": "rustformers/dolly-v2-ggml",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'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 "rustformers/dolly-v2-ggml" \
--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": "rustformers/dolly-v2-ggml",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'How to use rustformers/dolly-v2-ggml with Docker Model Runner:
docker model run hf.co/rustformers/dolly-v2-ggml
Dolly is trained on ~15k instruction/response fine tuning records databricks-dolly-15k generated by Databricks employees in capability domains from the InstructGPT paper, including brainstorming, classification, closed QA, generation, information extraction, open QA and summarization.
| Name | Based on | Type | Container | GGML Version |
|---|---|---|---|---|
| dolly-v2-12b-f16.bin | databricks/dolly-v2-12b | F16 | GGML | V3 |
| dolly-v2-12b-q4_0.bin | databricks/dolly-v2-12b | Q4_0 | GGML | V3 |
| dolly-v2-12b-q4_0-ggjt.bin | databricks/dolly-v2-12b | Q4_0 | GGJT | V3 |
| dolly-v2-3b-f16.bin | databricks/dolly-v2-3b | F16 | GGML | V3 |
| dolly-v2-3b-q4_0.bin | databricks/dolly-v2-3b | Q4_0 | GGML | V3 |
| dolly-v2-3b-q4_0-ggjt.bin | databricks/dolly-v2-3b | Q4_0 | GGJT | V3 |
| dolly-v2-3b-q5_1.bin | databricks/dolly-v2-3b | Q5_1 | GGML | V3 |
| dolly-v2-3b-q5_1-ggjt.bin | databricks/dolly-v2-3b | Q5_1 | GGJT | V3 |
| dolly-v2-7b-f16.bin | databricks/dolly-v2-7b | F16 | GGML | V3 |
| dolly-v2-7b-q4_0.bin | databricks/dolly-v2-7b | Q4_0 | GGML | V3 |
| dolly-v2-7b-q4_0-ggjt.bin | databricks/dolly-v2-7b | Q4_0 | GGJT | V3 |
| dolly-v2-7b-q5_1.bin | databricks/dolly-v2-7b | Q5_1 | GGML | V3 |
| dolly-v2-7b-q5_1-ggjt.bin | databricks/dolly-v2-7b | Q5_1 | GGJT | V3 |
Via pip: pip install llm-rs
from llm_rs import AutoModel
#Load the model, define any model you like from the list above as the `model_file`
model = AutoModel.from_pretrained("rustformers/dolly-v2-ggml",model_file="dolly-v2-12b-q4_0-ggjt.bin")
#Generate
print(model.generate("The meaning of life is"))
git clone --recurse-submodules https://github.com/rustformers/llm.git
cd llm
cargo build --release
cargo run --release -- gptneox infer -m path/to/model.bin -p "Tell me how cool the Rust programming language is:"
Install from pip and serve model
# Install vLLM from pip: pip install vllm# Start the vLLM server: vllm serve "rustformers/dolly-v2-ggml"# Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rustformers/dolly-v2-ggml", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'