Instructions to use eeshaAI/zeeb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use eeshaAI/zeeb with PEFT:

from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("EeshaAI/zeeb")
model = PeftModel.from_pretrained(base_model, "eeshaAI/zeeb")

Transformers

How to use eeshaAI/zeeb with Transformers:

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

pipe = pipeline("text-generation", model="eeshaAI/zeeb")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("eeshaAI/zeeb")
model = AutoModelForCausalLM.from_pretrained("eeshaAI/zeeb")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use eeshaAI/zeeb with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "eeshaAI/zeeb"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "eeshaAI/zeeb",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/eeshaAI/zeeb

SGLang

How to use eeshaAI/zeeb 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 "eeshaAI/zeeb" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "eeshaAI/zeeb",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "eeshaAI/zeeb" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "eeshaAI/zeeb",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use eeshaAI/zeeb with Docker Model Runner:
```
docker model run hf.co/eeshaAI/zeeb
```

eeshaAI commited on 18 days ago

Commit

dbe4dbf

verified ·

1 Parent(s): 0dc703b

Tokenizer with visual tokens

Browse files

Files changed (2) hide show

tokenizer.json +25 -26
tokenizer_config.json +7 -3

tokenizer.json CHANGED Viewed

@@ -1,21 +1,7 @@
 {
   "version": "1.0",
-  "truncation": {
-    "direction": "Right",
-    "max_length": 384,
-    "strategy": "LongestFirst",
-    "stride": 0
-  },
-  "padding": {
-    "strategy": {
-      "Fixed": 384
-    },
-    "direction": "Right",
-    "pad_to_multiple_of": null,
-    "pad_id": 100277,
-    "pad_type_id": 0,
-    "pad_token": "<|pad|>"
-  },
   "added_tokens": [
     {
       "id": 100256,
@@ -221,8 +207,8 @@
       "single_word": false,
       "lstrip": false,
       "rstrip": false,
-      "normalized": true,
-      "special": false
     },
     {
       "id": 100279,
@@ -230,8 +216,8 @@
       "single_word": false,
       "lstrip": false,
       "rstrip": false,
-      "normalized": true,
-      "special": false
     },
     {
       "id": 100280,
@@ -239,8 +225,8 @@
       "single_word": false,
       "lstrip": false,
       "rstrip": false,
-      "normalized": true,
-      "special": false
     },
     {
       "id": 100281,
@@ -9461,10 +9447,23 @@
   ],
   "normalizer": null,
   "pre_tokenizer": {
-    "type": "ByteLevel",
-    "add_prefix_space": false,
-    "trim_offsets": true,
-    "use_regex": true
   },
   "post_processor": {
     "type": "TemplateProcessing",

 {
   "version": "1.0",
+  "truncation": null,
+  "padding": null,
   "added_tokens": [
     {
       "id": 100256,
       "single_word": false,
       "lstrip": false,
       "rstrip": false,
+      "normalized": false,
+      "special": true
     },
     {
       "id": 100279,
       "single_word": false,
       "lstrip": false,
       "rstrip": false,
+      "normalized": false,
+      "special": true
     },
     {
       "id": 100280,
       "single_word": false,
       "lstrip": false,
       "rstrip": false,
+      "normalized": false,
+      "special": true
     },
     {
       "id": 100281,
   ],
   "normalizer": null,
   "pre_tokenizer": {
+    "type": "Sequence",
+    "pretokenizers": [
+      {
+        "type": "Split",
+        "pattern": {
+          "Regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+"
+        },
+        "behavior": "Removed",
+        "invert": true
+      },
+      {
+        "type": "ByteLevel",
+        "add_prefix_space": false,
+        "trim_offsets": true,
+        "use_regex": false
+      }
+    ]
   },
   "post_processor": {
     "type": "TemplateProcessing",

tokenizer_config.json CHANGED Viewed

@@ -4,11 +4,15 @@
   "bos_token": "<|endoftext|>",
   "clean_up_tokenization_spaces": false,
   "eos_token": "<|endoftext|>",
-  "errors": "replace",
   "is_local": false,
-  "local_files_only": false,
   "model_max_length": 1000000000000000019884624838656,
   "pad_token": "<|pad|>",
-  "tokenizer_class": "GPT2Tokenizer",
   "unk_token": "<|endoftext|>"
 }

   "bos_token": "<|endoftext|>",
   "clean_up_tokenization_spaces": false,
   "eos_token": "<|endoftext|>",
+  "extra_special_tokens": [
+    "<video_start>",
+    "<video_end>",
+    "<video_pad>"
+  ],
   "is_local": false,
   "model_max_length": 1000000000000000019884624838656,
+  "model_specific_special_tokens": {},
   "pad_token": "<|pad|>",
+  "tokenizer_class": "TokenizersBackend",
   "unk_token": "<|endoftext|>"
 }