Instructions to use actionpace/EvolCodeLlama-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use actionpace/EvolCodeLlama-7b with Transformers:

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

pipe = pipeline("text-generation", model="actionpace/EvolCodeLlama-7b")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("actionpace/EvolCodeLlama-7b")
model = AutoModelForCausalLM.from_pretrained("actionpace/EvolCodeLlama-7b")

llama-cpp-python

How to use actionpace/EvolCodeLlama-7b with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="actionpace/EvolCodeLlama-7b",
	filename="EvolCodeLlama-7b_Q8_0.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use actionpace/EvolCodeLlama-7b with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf actionpace/EvolCodeLlama-7b:Q8_0
# Run inference directly in the terminal:
llama-cli -hf actionpace/EvolCodeLlama-7b:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf actionpace/EvolCodeLlama-7b:Q8_0
# Run inference directly in the terminal:
llama-cli -hf actionpace/EvolCodeLlama-7b:Q8_0

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf actionpace/EvolCodeLlama-7b:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf actionpace/EvolCodeLlama-7b:Q8_0

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf actionpace/EvolCodeLlama-7b:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf actionpace/EvolCodeLlama-7b:Q8_0

Use Docker

docker model run hf.co/actionpace/EvolCodeLlama-7b:Q8_0

LM Studio
Jan

vLLM

How to use actionpace/EvolCodeLlama-7b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "actionpace/EvolCodeLlama-7b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "actionpace/EvolCodeLlama-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/actionpace/EvolCodeLlama-7b:Q8_0

SGLang

How to use actionpace/EvolCodeLlama-7b 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 "actionpace/EvolCodeLlama-7b" \
    --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": "actionpace/EvolCodeLlama-7b",
		"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 "actionpace/EvolCodeLlama-7b" \
        --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": "actionpace/EvolCodeLlama-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Ollama
How to use actionpace/EvolCodeLlama-7b with Ollama:
```
ollama run hf.co/actionpace/EvolCodeLlama-7b:Q8_0
```

Unsloth Studio new

How to use actionpace/EvolCodeLlama-7b 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 actionpace/EvolCodeLlama-7b 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 actionpace/EvolCodeLlama-7b to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for actionpace/EvolCodeLlama-7b to start chatting

Docker Model Runner
How to use actionpace/EvolCodeLlama-7b with Docker Model Runner:
```
docker model run hf.co/actionpace/EvolCodeLlama-7b:Q8_0
```

Lemonade

How to use actionpace/EvolCodeLlama-7b with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull actionpace/EvolCodeLlama-7b:Q8_0

Run and chat with the model

lemonade run user.EvolCodeLlama-7b-Q8_0

List all available models

lemonade list

actionpace commited on Nov 11, 2023

Commit

29de77b

1 Parent(s): 698d792

Upload tokenizer

Browse files

Files changed (3) hide show

special_tokens_map.json +9 -4
tokenizer.json +0 -0
tokenizer_config.json +49 -11

special_tokens_map.json CHANGED Viewed

@@ -1,23 +1,28 @@
 {
   "bos_token": {
     "content": "<s>",
     "lstrip": false,
-    "normalized": false,
     "rstrip": false,
     "single_word": false
   },
   "eos_token": {
     "content": "</s>",
     "lstrip": false,
-    "normalized": false,
     "rstrip": false,
     "single_word": false
   },
-  "pad_token": "</s>",
   "unk_token": {
     "content": "<unk>",
     "lstrip": false,
-    "normalized": false,
     "rstrip": false,
     "single_word": false
   }

 {
+  "additional_special_tokens": [
+    "▁<PRE>",
+    "▁<MID>",
+    "▁<SUF>",
+    "▁<EOT>"
+  ],
   "bos_token": {
     "content": "<s>",
     "lstrip": false,
+    "normalized": true,
     "rstrip": false,
     "single_word": false
   },
   "eos_token": {
     "content": "</s>",
     "lstrip": false,
+    "normalized": true,
     "rstrip": false,
     "single_word": false
   },
   "unk_token": {
     "content": "<unk>",
     "lstrip": false,
+    "normalized": true,
     "rstrip": false,
     "single_word": false
   }

tokenizer.json ADDED Viewed

The diff for this file is too large to render. See raw diff

tokenizer_config.json CHANGED Viewed

@@ -1,11 +1,9 @@
 {
-  "add_bos_token": true,
-  "add_eos_token": false,
   "added_tokens_decoder": {
     "0": {
       "content": "<unk>",
       "lstrip": false,
-      "normalized": false,
       "rstrip": false,
       "single_word": false,
       "special": true
@@ -13,7 +11,7 @@
     "1": {
       "content": "<s>",
       "lstrip": false,
-      "normalized": false,
       "rstrip": false,
       "single_word": false,
       "special": true
@@ -21,23 +19,63 @@
     "2": {
       "content": "</s>",
       "lstrip": false,
       "normalized": false,
       "rstrip": false,
       "single_word": false,
       "special": true
     }
   },
   "bos_token": "<s>",
   "clean_up_tokenization_spaces": false,
   "eos_token": "</s>",
-  "legacy": true,
   "model_max_length": 1000000000000000019884624838656,
-  "pad_token": "</s>",
   "sp_model_kwargs": {},
-  "spaces_between_special_tokens": false,
-  "tokenizer_class": "LlamaTokenizer",
-  "trust_remote_code": false,
   "unk_token": "<unk>",
-  "use_default_system_prompt": true,
-  "use_fast": true
 }

 {
   "added_tokens_decoder": {
     "0": {
       "content": "<unk>",
       "lstrip": false,
+      "normalized": true,
       "rstrip": false,
       "single_word": false,
       "special": true
     "1": {
       "content": "<s>",
       "lstrip": false,
+      "normalized": true,
       "rstrip": false,
       "single_word": false,
       "special": true
     "2": {
       "content": "</s>",
       "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32007": {
+      "content": "▁<PRE>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32008": {
+      "content": "▁<SUF>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32009": {
+      "content": "▁<MID>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32010": {
+      "content": "▁<EOT>",
+      "lstrip": false,
       "normalized": false,
       "rstrip": false,
       "single_word": false,
       "special": true
     }
   },
+  "additional_special_tokens": [
+    "▁<PRE>",
+    "▁<MID>",
+    "▁<SUF>",
+    "▁<EOT>"
+  ],
   "bos_token": "<s>",
   "clean_up_tokenization_spaces": false,
   "eos_token": "</s>",
+  "eot_token": "▁<EOT>",
+  "fill_token": "<FILL_ME>",
+  "legacy": null,
+  "middle_token": "▁<MID>",
   "model_max_length": 1000000000000000019884624838656,
+  "pad_token": null,
+  "prefix_token": "▁<PRE>",
   "sp_model_kwargs": {},
+  "suffix_token": "▁<SUF>",
+  "tokenizer_class": "CodeLlamaTokenizer",
   "unk_token": "<unk>",
+  "use_default_system_prompt": false
 }